diff --git a/doc/_templates/class.rst b/doc/_templates/class.rst
index f71c4d49..97a8a622 100644
--- a/doc/_templates/class.rst
+++ b/doc/_templates/class.rst
@@ -8,3 +8,8 @@
    {% block methods %}
    .. automethod:: __init__
    {% endblock %}
+
+.. _sphx_glr_backreferences_{{ fullname }}:
+
+.. minigallery:: {{ fullname }}
+    :add-heading:
diff --git a/doc/conf.py b/doc/conf.py
index be7d8fee..76c1cc67 100644
--- a/doc/conf.py
+++ b/doc/conf.py
@@ -18,8 +18,7 @@
 
 # mne update path
 import mne
-print(mne.datasets.sample.data_path(update_path=True))
-print(mne.datasets.eegbci.load_data(1, [6, 10, 14], update_path=True))
+print(mne.datasets.sample.data_path(update_path=True, download=False))
 
 matplotlib.use('Agg')
 import shlex
@@ -61,8 +60,11 @@
 plot_html_show_source_link = False
 
 sphinx_gallery_conf = {
-    'examples_dirs': ['../examples', '../tutorials'],
-    'gallery_dirs': ['auto_examples']
+    'examples_dirs': ['../examples'],
+    'gallery_dirs': ['auto_examples'],
+    'doc_module': 'pyriemann_qiskit',
+    'backreferences_dir': 'generated',
+    'plot_gallery': 'True',
 }
 # Add any paths that contain templates here, relative to this directory.
 templates_path = ['_templates']
diff --git a/doc/introduction.rst b/doc/introduction.rst
index 3a35805d..ae2b10bf 100644
--- a/doc/introduction.rst
+++ b/doc/introduction.rst
@@ -80,4 +80,4 @@ References
 
 How to cite?
 ================================
-Anton Andreev, Grégoire Cattan, Sylvain Chevallier, and Quentin Barthélemy. ‘PyRiemann-Qiskit: A Sandbox for Quantum Classification Experiments with Riemannian Geometry’. Research Ideas and Outcomes 9 (20 March 2023). https://doi.org/10.3897/rio.9.e101006.
+Anton Andreev, Grégoire Cattan, Sylvain Chevallier, and Quentin Barthélemy. ‘pyRiemann-qiskit: A Sandbox for Quantum Classification Experiments with Riemannian Geometry’. Research Ideas and Outcomes 9 (20 March 2023). https://doi.org/10.3897/rio.9.e101006.
diff --git a/examples/ERP/noplot_classify_P300_bi_illiteracy.py b/examples/ERP/noplot_classify_P300_bi_illiteracy.py
index 5bde4378..6451dd89 100644
--- a/examples/ERP/noplot_classify_P300_bi_illiteracy.py
+++ b/examples/ERP/noplot_classify_P300_bi_illiteracy.py
@@ -12,24 +12,25 @@
 # License: BSD (3-clause)
 
 from enum import Enum
-from matplotlib import pyplot as plt
-import numpy as np
-import seaborn as sns
 import warnings
 
+from matplotlib import pyplot as plt
 from mne.decoding import Vectorizer
 from moabb import set_log_level
 from moabb.datasets.compound_dataset import BI_Il
 from moabb.evaluations import WithinSessionEvaluation
 from moabb.paradigms import P300
+import numpy as np
 from pyriemann.estimation import XdawnCovariances
 from pyriemann.tangentspace import TangentSpace
 from pyriemann.classification import MDM
 from pyriemann.spatialfilters import Xdawn
+import seaborn as sns
 from sklearn.ensemble import VotingClassifier
 from sklearn.pipeline import make_pipeline, Pipeline
 from sklearn.discriminant_analysis import LinearDiscriminantAnalysis as LDA
 from sklearn.svm import SVC
+
 from pyriemann_qiskit.ensemble import JudgeClassifier
 
 # inject convex distance and mean to pyriemann (if not done already)
@@ -40,7 +41,6 @@
     QuantumClassifierWithDefaultRiemannianPipeline,
 )
 
-
 print(__doc__)
 
 
diff --git a/examples/ERP/noplot_classify_P300_bi_quantum_mdm.py b/examples/ERP/noplot_classify_P300_bi_quantum_mdm.py
index a9209853..5a6e9618 100644
--- a/examples/ERP/noplot_classify_P300_bi_quantum_mdm.py
+++ b/examples/ERP/noplot_classify_P300_bi_quantum_mdm.py
@@ -23,9 +23,9 @@
 # Modified from plot_classify_EEG_tangentspace.py of pyRiemann
 # License: BSD (3-clause)
 
-from matplotlib import pyplot as plt
 import warnings
-import seaborn as sns
+
+from matplotlib import pyplot as plt
 from moabb import set_log_level
 from moabb.datasets import (
     # bi2012,
@@ -42,6 +42,7 @@
 )
 from moabb.evaluations import WithinSessionEvaluation
 from moabb.paradigms import P300
+import seaborn as sns
 
 # inject cpm distance and mean to pyriemann (if not done already)
 from pyriemann_qiskit.utils import distance, mean  # noqa
diff --git a/examples/ERP/noplot_firebase_moabb.py b/examples/ERP/noplot_firebase_moabb.py
index 5dca7bac..6b85bb32 100644
--- a/examples/ERP/noplot_firebase_moabb.py
+++ b/examples/ERP/noplot_firebase_moabb.py
@@ -23,27 +23,29 @@
 # Modified from plot_classify_P300_bi.py
 # License: BSD (3-clause)
 
+import warnings
+
+from matplotlib import pyplot as plt
+from moabb import set_log_level
+from moabb.datasets import bi2012
+from moabb.evaluations import WithinSessionEvaluation
+from moabb.paradigms import P300
 from pyriemann.estimation import XdawnCovariances
 from pyriemann.tangentspace import TangentSpace
+import seaborn as sns
+from sklearn.discriminant_analysis import LinearDiscriminantAnalysis as LDA
+from sklearn.pipeline import make_pipeline
+from sklearn.decomposition import PCA
+
 from pyriemann_qiskit.utils import (
     generate_caches,
     filter_subjects_by_incomplete_results,
     add_moabb_dataframe_results_to_caches,
     convert_caches_to_dataframes,
 )
-from sklearn.pipeline import make_pipeline
-from matplotlib import pyplot as plt
-import warnings
-import seaborn as sns
-from sklearn.discriminant_analysis import LinearDiscriminantAnalysis as LDA
-from moabb import set_log_level
-from moabb.datasets import bi2012
-from moabb.evaluations import WithinSessionEvaluation
-from moabb.paradigms import P300
 from pyriemann_qiskit.pipelines import (
     QuantumClassifierWithDefaultRiemannianPipeline,
 )
-from sklearn.decomposition import PCA
 
 print(__doc__)
 
diff --git a/examples/ERP/plot_classify_EEG_quantum_svm.py b/examples/ERP/plot_classify_EEG_quantum_svm.py
index 1b0cc25b..eb6babfc 100644
--- a/examples/ERP/plot_classify_EEG_quantum_svm.py
+++ b/examples/ERP/plot_classify_EEG_quantum_svm.py
@@ -13,11 +13,9 @@
 # Modified from plot_classify_EEG_tangentspace.py of pyRiemann
 # License: BSD (3-clause)
 
+from matplotlib import pyplot as plt
 from pyriemann.estimation import XdawnCovariances
 from pyriemann.tangentspace import TangentSpace
-from pyriemann_qiskit.classification import QuanticSVM
-from pyriemann_qiskit.utils.filtering import NaiveDimRed
-from pyriemann_qiskit.datasets import get_mne_sample
 from sklearn.pipeline import make_pipeline
 from sklearn.model_selection import train_test_split
 from sklearn.metrics import (
@@ -25,11 +23,14 @@
     ConfusionMatrixDisplay,
     balanced_accuracy_score,
 )
-from matplotlib import pyplot as plt
 
+from pyriemann_qiskit.classification import QuanticSVM
+from pyriemann_qiskit.utils.filtering import NaiveDimRed
+from pyriemann_qiskit.datasets import get_mne_sample
 
 print(__doc__)
 
+##############################################################################
 
 X, y = get_mne_sample(n_trials=-1)
 
diff --git a/examples/ERP/plot_classify_P300_bi.py b/examples/ERP/plot_classify_P300_bi.py
index a5ea971d..a8c70930 100644
--- a/examples/ERP/plot_classify_P300_bi.py
+++ b/examples/ERP/plot_classify_P300_bi.py
@@ -22,21 +22,23 @@
 # Modified from plot_classify_EEG_tangentspace.py of pyRiemann
 # License: BSD (3-clause)
 
-from pyriemann.estimation import XdawnCovariances
-from pyriemann.tangentspace import TangentSpace
-from sklearn.pipeline import make_pipeline
-from matplotlib import pyplot as plt
 import warnings
-import seaborn as sns
-from sklearn.discriminant_analysis import LinearDiscriminantAnalysis as LDA
+
+from matplotlib import pyplot as plt
 from moabb import set_log_level
 from moabb.datasets import bi2012
 from moabb.evaluations import WithinSessionEvaluation
 from moabb.paradigms import P300
+from pyriemann.estimation import XdawnCovariances
+from pyriemann.tangentspace import TangentSpace
+import seaborn as sns
+from sklearn.pipeline import make_pipeline
+from sklearn.discriminant_analysis import LinearDiscriminantAnalysis as LDA
+from sklearn.decomposition import PCA
+
 from pyriemann_qiskit.pipelines import (
     QuantumClassifierWithDefaultRiemannianPipeline,
 )
-from sklearn.decomposition import PCA
 
 print(__doc__)
 
diff --git a/examples/MI/noplot_classify_alexmi_with_quantum_pipeline.py b/examples/MI/noplot_classify_alexmi_with_quantum_pipeline.py
index 5baf62b5..7fa6461c 100644
--- a/examples/MI/noplot_classify_alexmi_with_quantum_pipeline.py
+++ b/examples/MI/noplot_classify_alexmi_with_quantum_pipeline.py
@@ -12,13 +12,14 @@
 # Modified from ERP/classify_P300_bi_quantum_mdm.py
 # License: BSD (3-clause)
 
-from matplotlib import pyplot as plt
 import warnings
-import seaborn as sns
+
+from matplotlib import pyplot as plt
 from moabb import set_log_level
 from moabb.datasets import AlexMI
 from moabb.evaluations import WithinSessionEvaluation
 from moabb.paradigms import MotorImagery
+import seaborn as sns
 
 # inject cpm distance and mean to pyriemann (if not done already)
 from helpers.alias import ERPCov_MDM
diff --git a/examples/MI/noplot_multiclass_classification.py b/examples/MI/noplot_multiclass_classification.py
index 722045d6..0076c3c9 100644
--- a/examples/MI/noplot_multiclass_classification.py
+++ b/examples/MI/noplot_multiclass_classification.py
@@ -13,12 +13,7 @@
 # Modified from plot_classify_EEG_quantum_svm
 # License: BSD (3-clause)
 
-from helpers.alias import ERPCov_MDM
-from pyriemann_qiskit.datasets import get_mne_sample
-from pyriemann_qiskit.pipelines import (
-    QuantumClassifierWithDefaultRiemannianPipeline,
-    QuantumMDMWithRiemannianPipeline,
-)
+from matplotlib import pyplot as plt
 from sklearn.model_selection import train_test_split
 from sklearn.metrics import (
     confusion_matrix,
@@ -26,8 +21,13 @@
     balanced_accuracy_score,
 )
 from sklearn.decomposition import PCA
-from matplotlib import pyplot as plt
 
+from helpers.alias import ERPCov_MDM
+from pyriemann_qiskit.datasets import get_mne_sample
+from pyriemann_qiskit.pipelines import (
+    QuantumClassifierWithDefaultRiemannianPipeline,
+    QuantumMDMWithRiemannianPipeline,
+)
 
 print(__doc__)
 
diff --git a/examples/MI/plot_compare_dim_red.py b/examples/MI/plot_compare_dim_red.py
index 48febbb9..7eb677e0 100644
--- a/examples/MI/plot_compare_dim_red.py
+++ b/examples/MI/plot_compare_dim_red.py
@@ -19,16 +19,19 @@
 # Author: Gregoire Cattan
 # License: BSD (3-clause)
 
+from sklearn.decomposition import PCA
+from sklearn.model_selection import StratifiedKFold, GridSearchCV
+
 from pyriemann_qiskit.datasets import get_mne_sample
 from pyriemann_qiskit.pipelines import (
     QuantumClassifierWithDefaultRiemannianPipeline,
 )
 from pyriemann_qiskit.utils.filtering import NaiveDimRed
-from sklearn.decomposition import PCA
-from sklearn.model_selection import StratifiedKFold, GridSearchCV
 
 print(__doc__)
 
+###############################################################################
+
 X, y = get_mne_sample(n_trials=10)
 
 default_params = {
diff --git a/examples/other_datasets/plot_financial_data.py b/examples/other_datasets/plot_financial_data.py
index 797006bf..9c75f36c 100644
--- a/examples/other_datasets/plot_financial_data.py
+++ b/examples/other_datasets/plot_financial_data.py
@@ -30,26 +30,27 @@
 # Authors: Gregoire Cattan, Filipe Barroso
 # License: BSD (3-clause)
 
+import os
+import warnings
+
+from imblearn.under_sampling import NearMiss
+from matplotlib import pyplot as plt
+import numpy as np
+import pandas as pd
+from pyriemann.preprocessing import Whitening
+from pyriemann.estimation import XdawnCovariances
+from pyriemann.utils.viz import plot_waveforms
 from sklearn.base import TransformerMixin, BaseEstimator, ClassifierMixin
 from sklearn.experimental import enable_halving_search_cv  # noqa
-from sklearn.model_selection import HalvingGridSearchCV
+from sklearn.model_selection import HalvingGridSearchCV, train_test_split
 from sklearn.pipeline import make_pipeline
-from sklearn.model_selection import train_test_split
 from sklearn.preprocessing import LabelEncoder
 from sklearn.ensemble import RandomForestClassifier
 from sklearn.svm import SVC
 from sklearn.metrics import balanced_accuracy_score
-from imblearn.under_sampling import NearMiss
-from pyriemann.preprocessing import Whitening
-from pyriemann.estimation import XdawnCovariances
-from pyriemann.utils.viz import plot_waveforms
+
 from pyriemann_qiskit.classification import QuanticSVM
 from pyriemann_qiskit.utils.preprocessing import NdRobustScaler
-from matplotlib import pyplot as plt
-import warnings
-import pandas as pd
-import numpy as np
-import os
 
 print(__doc__)
 
@@ -86,7 +87,6 @@ def plot_ERP(X, title, n=10, ylim=None, add_digest=False):
 
 
 def merge_2axes(fig1, fig2, file_name1="f1.png", file_name2="f2.png"):
-    # Modified from [4]
     fig1.savefig(file_name1)
     fig2.savefig(file_name2)
     plt.close(fig1)
@@ -466,5 +466,3 @@ def predict(self, X):
 # .. [2] 'Synthetic Data of Transactions for Inmediate Loans Fraud'
 #         https://zenodo.org/records/7418458
 # .. [3] https://pyriemann.readthedocs.io/en/latest/auto_examples/ERP/plot_ERP.html
-#
-# .. [4] https://stackoverflow.com/questions/16748577
diff --git a/examples/other_datasets/plot_tutorial_quantum_svm_titanic_data.py b/examples/other_datasets/plot_tutorial_quantum_svm_titanic_data.py
index 6208f988..9909c5cb 100644
--- a/examples/other_datasets/plot_tutorial_quantum_svm_titanic_data.py
+++ b/examples/other_datasets/plot_tutorial_quantum_svm_titanic_data.py
@@ -10,10 +10,10 @@
 # Author: Adrien Veres
 # License: BSD (3-clause)
 
+import matplotlib.pyplot as plt
 import numpy as np
 import pandas as pd
 import seaborn as sns
-import matplotlib.pyplot as plt
 from sklearn.impute import KNNImputer
 from sklearn.preprocessing import LabelEncoder, StandardScaler
 from sklearn.decomposition import PCA
@@ -21,6 +21,7 @@
 from sklearn.linear_model import LogisticRegression
 from sklearn.svm import SVC
 from sklearn.metrics import balanced_accuracy_score
+
 from pyriemann_qiskit.classification import QuanticSVM
 
 print(__doc__)
diff --git a/examples/toys_dataset/plot_classifier_comparison.py b/examples/toys_dataset/plot_classifier_comparison.py
index cef7c1ee..5c9afac2 100644
--- a/examples/toys_dataset/plot_classifier_comparison.py
+++ b/examples/toys_dataset/plot_classifier_comparison.py
@@ -12,13 +12,14 @@
 # Modified for pyRiemann-qiskit by Gregoire Cattan
 # License: BSD 3 clause
 
-import numpy as np
 import matplotlib.pyplot as plt
 from matplotlib.colors import ListedColormap
+import numpy as np
 from sklearn.model_selection import train_test_split
 from sklearn.preprocessing import StandardScaler
 from sklearn.datasets import make_moons, make_circles
 from sklearn.svm import SVC
+
 from pyriemann_qiskit.datasets import (
     generate_linearly_separable_dataset,
     generate_qiskit_dataset,
diff --git a/examples/toys_dataset/plot_learning_curve.py b/examples/toys_dataset/plot_learning_curve.py
index 544fe35d..3fadf8d1 100644
--- a/examples/toys_dataset/plot_learning_curve.py
+++ b/examples/toys_dataset/plot_learning_curve.py
@@ -11,13 +11,15 @@
 # Author: Gregoire Cattan
 # License: BSD (3-clause)
 
+import matplotlib.pyplot as plt
+from pyriemann.estimation import Shrinkage
+
 from pyriemann_qiskit.datasets.utils import get_mne_sample
 from pyriemann_qiskit.pipelines import QuantumMDMWithRiemannianPipeline
 from pyriemann_qiskit.utils.hyper_params_factory import get_spsa
-import matplotlib.pyplot as plt
 from pyriemann_qiskit.datasets import generate_linearly_separable_dataset
 from pyriemann_qiskit.classification import QuanticVQC
-from pyriemann.estimation import Shrinkage
+
 
 print(__doc__)
 
diff --git a/examples/toys_dataset/plot_qaoa_cv.py b/examples/toys_dataset/plot_qaoa_cv.py
index 98d4b0d0..2dfee07c 100644
--- a/examples/toys_dataset/plot_qaoa_cv.py
+++ b/examples/toys_dataset/plot_qaoa_cv.py
@@ -4,7 +4,7 @@
 ====================================================================
 
 QAOA is a parametric quantum circuit, which is usually used to
-solve QUBO problems, i.e, problems with binary variables.
+solve QUBO problems, i.e, problems with binary variables [1]_.
 
 In this example we will show how to use pyRiemann-qiskit implementation
 of QAOA-CV, which accepts continuous variables.
@@ -18,22 +18,22 @@
 
 from docplex.mp.model import Model
 import matplotlib.pyplot as plt
+from qiskit.primitives import BackendSampler
+from qiskit_aer import AerSimulator
+from qiskit_algorithms.optimizers import COBYLA, SPSA
+
+from pyriemann_qiskit.utils.docplex import QAOACVOptimizer
 from pyriemann_qiskit.utils.hyper_params_factory import (
     create_mixer_rotational_X_gates,
     create_mixer_rotational_XY_gates,
     create_mixer_rotational_XZ_gates,
 )
-from qiskit.primitives import BackendSampler
-from qiskit_aer import AerSimulator
-from qiskit_algorithms.optimizers import COBYLA, SPSA
-from pyriemann_qiskit.utils.docplex import QAOACVOptimizer
 
 
 ###############################################################################
 # Run QAOA-CV
 #
 # Let's define a handy function to run and plot the result of the QAOA-CV
-#
 
 
 def run_qaoa_cv(n_reps, optimizer, create_mixer):
@@ -81,7 +81,6 @@ def run_qaoa_cv(n_reps, optimizer, create_mixer):
 # a cost an mixer operator.
 #
 # We will now try different combination of optimizer and mixers.
-#
 
 maxiter = 500
 optimizers = [
@@ -118,4 +117,3 @@ def run_qaoa_cv(n_reps, optimizer, create_mixer):
 # References
 # ----------
 # .. [1] https://dice.cyfronet.pl/papers/JPlewa_JSienko_msc_v2.pdf
-#
diff --git a/examples/toys_dataset/plot_quantum_art_vqc.py b/examples/toys_dataset/plot_quantum_art_vqc.py
index 987ddd78..611b31ca 100644
--- a/examples/toys_dataset/plot_quantum_art_vqc.py
+++ b/examples/toys_dataset/plot_quantum_art_vqc.py
@@ -11,8 +11,9 @@
 # Author: Gregoire Cattan
 # License: BSD (3-clause)
 
-from pyriemann_qiskit.utils.hyper_params_factory import gen_two_local
 import matplotlib.pyplot as plt
+
+from pyriemann_qiskit.utils.hyper_params_factory import gen_two_local
 from pyriemann_qiskit.datasets import generate_linearly_separable_dataset
 from pyriemann_qiskit.classification import QuanticVQC
 from pyriemann_qiskit.visualization import weights_spiral
diff --git a/pyriemann_qiskit/classification.py b/pyriemann_qiskit/classification.py
index c629e69c..f1011f10 100644
--- a/pyriemann_qiskit/classification.py
+++ b/pyriemann_qiskit/classification.py
@@ -5,38 +5,46 @@
 quantum computer.
 """
 from datetime import datetime
-from pyriemann_qiskit.utils.quantum_provider import get_quantum_kernel
-from scipy.special import softmax
 import logging
-import numpy as np
+import random
 from warnings import warn
 
-from sklearn.base import BaseEstimator, ClassifierMixin, TransformerMixin
-from pyriemann.utils.distance import distance
+from joblib import Parallel, delayed
+import numpy as np
 from pyriemann.classification import MDM
-from pyriemann_qiskit.datasets import get_feature_dimension
-from pyriemann_qiskit.utils import (
-    ClassicalOptimizer,
-    NaiveQAOAOptimizer,
-    set_global_optimizer,
-)
-from pyriemann_qiskit.utils.distance import distance_functions
-from pyriemann_qiskit.utils.utils import is_qfunction
+from pyriemann.utils.distance import distance
 from qiskit.primitives import BackendSampler
+from qiskit_algorithms.optimizers import SLSQP
 from qiskit_ibm_runtime import QiskitRuntimeService
 from qiskit_machine_learning.algorithms import QSVC, VQC, PegasosQSVC
 from qiskit_optimization.algorithms import (
     CobylaOptimizer,
     SlsqpOptimizer,
 )
-from qiskit_algorithms.optimizers import SLSQP
+from scipy.special import softmax
+from sklearn.base import BaseEstimator, ClassifierMixin, TransformerMixin
 from sklearn.svm import SVC
 
-from .utils.hyper_params_factory import gen_zz_feature_map, gen_two_local, get_spsa
-from .utils import get_provider, get_device, get_simulator
-from .utils.distance import qdistance_logeuclid_to_convex_hull
-from joblib import Parallel, delayed
-import random
+from .datasets import get_feature_dimension
+from .utils import (
+    get_provider,
+    get_device,
+    get_simulator,
+    set_global_optimizer,
+    ClassicalOptimizer,
+    NaiveQAOAOptimizer,
+)
+from .utils.distance import (
+    distance_functions,
+    qdistance_logeuclid_to_convex_hull,
+)
+from .utils.hyper_params_factory import (
+    gen_zz_feature_map,
+    gen_two_local,
+    get_spsa,
+)
+from .utils.quantum_provider import get_quantum_kernel
+from .utils.utils import is_qfunction
 
 logging.basicConfig(level=logging.WARNING)
 
@@ -506,7 +514,7 @@ class QuanticVQC(QuanticClassifierBase):
     .. versionchanged:: 0.2.0
         Add seed parameter
     .. versionchanged:: 0.3.0
-        Add evaluated_values_ attribute.
+        Add `evaluated_values_` attribute.
 
     See Also
     --------
@@ -1033,7 +1041,7 @@ class QuanticNCH(QuanticClassifierBase):
     regularization : MixinTransformer | None, default=None
         Additional post-processing to regularize means.
     classical_optimizer : OptimizationAlgorithm, default=SlsqpOptimizer()
-        An instance of OptimizationAlgorithm [3]_.
+        An instance of OptimizationAlgorithm [1]_.
     n_jobs : int, default=6
         The number of jobs to use for the computation. This works by computing
         each of the hulls in parallel.
@@ -1050,6 +1058,10 @@ class QuanticNCH(QuanticClassifierBase):
         An instance of a scipy optimizer to find the optimal weights for the
         parametric circuit (ansatz).
 
+    References
+    ----------
+    .. [1] \
+        https://qiskit-community.github.io/qiskit-optimization/stubs/qiskit_optimization.algorithms.OptimizationAlgorithm.html#optimizationalgorithm
     """
 
     def __init__(
diff --git a/pyriemann_qiskit/datasets/utils.py b/pyriemann_qiskit/datasets/utils.py
index 52013e7a..45fe4d06 100644
--- a/pyriemann_qiskit/datasets/utils.py
+++ b/pyriemann_qiskit/datasets/utils.py
@@ -2,13 +2,13 @@
 Contains helper methods and classes to manage datasets.
 """
 from warnings import warn
-import numpy as np
 
 try:
     from mne import io, read_events, pick_types, Epochs
     from mne.datasets import sample
 except Exception:
     warn("mne not available. get_mne_sample will fail.")
+import numpy as np
 from qiskit_machine_learning.datasets import ad_hoc_data
 from sklearn.datasets import make_classification
 
diff --git a/pyriemann_qiskit/ensemble.py b/pyriemann_qiskit/ensemble.py
index e50feed2..50c1ef45 100644
--- a/pyriemann_qiskit/ensemble.py
+++ b/pyriemann_qiskit/ensemble.py
@@ -2,9 +2,10 @@
 Ensemble classifiers.
 """
 import numpy as np
-from pyriemann_qiskit.utils import union_of_diff
 from sklearn.base import ClassifierMixin, BaseEstimator
 
+from .utils import union_of_diff
+
 
 class JudgeClassifier(BaseEstimator, ClassifierMixin):
 
@@ -19,13 +20,12 @@ class JudgeClassifier(BaseEstimator, ClassifierMixin):
 
     Parameters
     ----------
-    clfs : ClassifierMixin[]
-        A list of ClassifierMixin.
-
     judge : ClassifierMixin
-        An instance of ClassifierMixin.
-        This classifier is trained on the labels for which
-        classifiers clfs obtain different predictions.
+        Classifier trained on the inputs for which
+        classifiers `clfs` obtain different predictions.
+
+    clfs : list of ClassifierMixin
+        Classifiers trained on the balanced dataset.
 
     Notes
     -----
diff --git a/pyriemann_qiskit/pipelines.py b/pyriemann_qiskit/pipelines.py
index dd6459ce..d643fa8e 100644
--- a/pyriemann_qiskit/pipelines.py
+++ b/pyriemann_qiskit/pipelines.py
@@ -1,30 +1,31 @@
 """Module for pipelines."""
 import numpy as np
+from pyriemann.classification import MDM
+from pyriemann.estimation import XdawnCovariances, ERPCovariances
+from pyriemann.preprocessing import Whitening
+from pyriemann.tangentspace import TangentSpace
+from qiskit_algorithms.optimizers import SLSQP
+from qiskit_optimization.algorithms import SlsqpOptimizer
 from sklearn.base import BaseEstimator, ClassifierMixin, TransformerMixin
 from sklearn.decomposition import PCA
 from sklearn.discriminant_analysis import LinearDiscriminantAnalysis as LDA
 from sklearn.pipeline import make_pipeline, FeatureUnion
 from sklearn.ensemble import VotingClassifier
-from qiskit_optimization.algorithms import SlsqpOptimizer
-from qiskit_algorithms.optimizers import SLSQP
-from pyriemann.estimation import XdawnCovariances, ERPCovariances
-from pyriemann.tangentspace import TangentSpace
-from pyriemann.preprocessing import Whitening
-from pyriemann.classification import MDM
-from pyriemann_qiskit.utils.utils import is_qfunction
-from pyriemann_qiskit.utils.filtering import NoDimRed
-from pyriemann_qiskit.utils.hyper_params_factory import (
-    # gen_zz_feature_map,
-    gen_x_feature_map,
-    gen_two_local,
-    get_spsa,
-)
-from pyriemann_qiskit.classification import (
+
+from .classification import (
     QuanticNCH,
     QuanticVQC,
     QuanticSVM,
     QuanticMDM,
 )
+from .utils.filtering import NoDimRed
+from .utils.hyper_params_factory import (
+    # gen_zz_feature_map,
+    gen_x_feature_map,
+    gen_two_local,
+    get_spsa,
+)
+from .utils.utils import is_qfunction
 
 
 class BasePipeline(BaseEstimator, ClassifierMixin, TransformerMixin):
diff --git a/pyriemann_qiskit/utils/distance.py b/pyriemann_qiskit/utils/distance.py
index eedbdfc5..fb49b2e9 100644
--- a/pyriemann_qiskit/utils/distance.py
+++ b/pyriemann_qiskit/utils/distance.py
@@ -1,6 +1,7 @@
-import numpy as np
+from typing_extensions import deprecated
+
 from docplex.mp.model import Model
-from pyriemann_qiskit.utils.docplex import ClassicalOptimizer, get_global_optimizer
+import numpy as np
 from pyriemann.utils.distance import (
     distance_functions,
     distance_logeuclid,
@@ -8,7 +9,8 @@
 )
 from pyriemann.utils.base import logm
 from pyriemann.utils.mean import mean_logeuclid
-from typing_extensions import deprecated
+
+from .docplex import ClassicalOptimizer, get_global_optimizer
 
 
 @deprecated(
diff --git a/pyriemann_qiskit/utils/docplex.py b/pyriemann_qiskit/utils/docplex.py
index db80e1af..10a016a3 100644
--- a/pyriemann_qiskit/utils/docplex.py
+++ b/pyriemann_qiskit/utils/docplex.py
@@ -8,11 +8,12 @@
 import math
 import time
 
-import numpy as np
 from docplex.mp.vartype import ContinuousVarType, IntegerVarType, BinaryVarType
+import numpy as np
+from pyriemann.utils.covariance import normalize
+from qiskit.circuit.library import QAOAAnsatz
 from qiskit.primitives import BackendSampler
 from qiskit.quantum_info import Statevector
-from qiskit.circuit.library import QAOAAnsatz
 from qiskit_algorithms import QAOA
 from qiskit_algorithms.optimizers import SLSQP
 from qiskit_optimization.algorithms import CobylaOptimizer, MinimumEigenOptimizer
@@ -20,8 +21,8 @@
 from qiskit_optimization.translators import from_docplex_mp
 from qiskit_optimization.problems import VarType
 from sklearn.preprocessing import MinMaxScaler
-from pyriemann.utils.covariance import normalize
-from pyriemann_qiskit.utils import get_simulator
+
+from .quantum_provider import get_simulator
 
 
 _global_optimizer = [None]
@@ -438,7 +439,7 @@ class NaiveQAOAOptimizer(pyQiskitOptimizer):
     .. versionchanged:: 0.0.4
         add get_weights method.
     .. versionchanged:: 0.3.0
-        add evaluated_values_ attribute.
+        add `evaluated_values_` attribute.
         add optimizer parameter.
 
     Attributes
diff --git a/pyriemann_qiskit/utils/firebase_connector.py b/pyriemann_qiskit/utils/firebase_connector.py
index b88574ae..e84a16c5 100644
--- a/pyriemann_qiskit/utils/firebase_connector.py
+++ b/pyriemann_qiskit/utils/firebase_connector.py
@@ -1,6 +1,5 @@
 import firebase_admin
 import os
-import pandas as pd
 from warnings import warn
 
 try:
@@ -10,6 +9,9 @@
         """No firebase_admin found. Firebase connector \
          can only run with mock data."""
     )
+
+import pandas as pd
+
 from .firebase_cert import certificate
 
 
diff --git a/pyriemann_qiskit/utils/math.py b/pyriemann_qiskit/utils/math.py
index c1fd62c3..39296767 100644
--- a/pyriemann_qiskit/utils/math.py
+++ b/pyriemann_qiskit/utils/math.py
@@ -1,5 +1,6 @@
 """Module for mathematical helpers"""
 from typing_extensions import deprecated
+
 import numpy as np
 from pyriemann.utils.covariance import normalize
 
diff --git a/pyriemann_qiskit/utils/mean.py b/pyriemann_qiskit/utils/mean.py
index a11c642f..a91e056f 100644
--- a/pyriemann_qiskit/utils/mean.py
+++ b/pyriemann_qiskit/utils/mean.py
@@ -1,10 +1,12 @@
 from typing_extensions import deprecated
+
 from docplex.mp.model import Model
-from pyriemann.utils.mean import mean_functions
-from pyriemann_qiskit.utils.docplex import ClassicalOptimizer, get_global_optimizer
 from pyriemann.utils.base import logm, expm
+from pyriemann.utils.mean import mean_functions
 from qiskit_optimization.algorithms import ADMMOptimizer
 
+from .docplex import ClassicalOptimizer, get_global_optimizer
+
 
 @deprecated(
     "fro_mean_convex is deprecated and will be removed in 0.3.0; "
diff --git a/pyriemann_qiskit/utils/quantum_provider.py b/pyriemann_qiskit/utils/quantum_provider.py
index 66c4cf84..10e1fe9f 100644
--- a/pyriemann_qiskit/utils/quantum_provider.py
+++ b/pyriemann_qiskit/utils/quantum_provider.py
@@ -1,15 +1,16 @@
 """Module containing helpers for IBM quantum backends
    providers and simulators."""
 
-from qiskit_ibm_runtime import QiskitRuntimeService
+import logging
+
 from qiskit_aer import AerSimulator
 from qiskit_aer.quantum_info import AerStatevector
+from qiskit_algorithms.state_fidelities import ComputeUncompute
+from qiskit_ibm_runtime import QiskitRuntimeService
 from qiskit_machine_learning.kernels import (
     FidelityStatevectorKernel,
     FidelityQuantumKernel,
 )
-from qiskit_algorithms.state_fidelities import ComputeUncompute
-import logging
 
 
 def get_provider():
diff --git a/pyriemann_qiskit/visualization/art.py b/pyriemann_qiskit/visualization/art.py
index 2e4aff42..3ace3884 100644
--- a/pyriemann_qiskit/visualization/art.py
+++ b/pyriemann_qiskit/visualization/art.py
@@ -2,8 +2,8 @@
 Artistic visualization for quantum.
 """
 
-import pandas as pd
 import numpy as np
+import pandas as pd
 
 
 def weights_spiral(axe, vqc, X, y, n_trainings=5):
diff --git a/pyriemann_qiskit/visualization/manifold.py b/pyriemann_qiskit/visualization/manifold.py
index 83a5a54d..8338ef89 100644
--- a/pyriemann_qiskit/visualization/manifold.py
+++ b/pyriemann_qiskit/visualization/manifold.py
@@ -2,11 +2,12 @@
 Visualization of the covariance matrices on the SPD manifold.
 """
 
-import numpy as np
 import matplotlib.pyplot as plt
-from pyriemann_qiskit.utils.math import to_xyz
+import numpy as np
 from scipy.spatial import ConvexHull
 
+from ..utils.math import to_xyz
+
 
 def plot_cvx_hull(X, ax):
     """Plot the convex hull of a set of points.