Interpretable End-to-end Urban Autonomous Driving with Latent Deep Reinforcement Learning
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Mar 24, 2023 - Python
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latent-representations
Here are 21 public repositories matching this topic...
Implementation of "Disentangled Representation Learning for Non-Parallel Text Style Transfer(ACL 2019)" in Pytorch
acl pytorch style-transfer natural-language-generation adversarial-learning variational-autoencoder disentanglement disentangled-representations text-style-transfer latent-representations
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Oct 25, 2024 - Python
Graph Representation Analysis for Connected Embeddings
data-science machine-learning computer-vision image-processing feature-extraction neural-networks object-detection graphical-models latent-representations
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Oct 10, 2024 - Jupyter Notebook
This repository contains the implementation of SimplEx, a method to explain the latent representations of black-box models with the help of a corpus of examples. For more details, please read our NeurIPS 2021 paper: 'Explaining Latent Representations with a Corpus of Examples'.
machine-learning artificial-intelligence neural-networks method interpretability feature-importance explainable-ai latent-space latent-representations neurips example-based-explanations neurips-2021
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Jan 31, 2023 - Python
Code for our paper -- Hyperprior Induced Unsupervised Disentanglement of Latent Representations (AAAI 2019)
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Jan 16, 2019 - Python
ACM CHIL 2020: "Survival Cluster Analysis"
deep-learning clustering survival-analysis dirichlet-process time-to-event bayesian-nonparametrics latent-representations
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Jan 26, 2021 - Jupyter Notebook
ICCV23 "Householder Projector for Unsupervised Latent Semantics Discovery"
generative-adversarial-network latent-semantic-analysis disentangled-representations latent-representations
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Dec 27, 2024 - Jupyter Notebook
Tripod is a tool/ML model for computing latent representations for large sequences
machine-learning machine-learning-algorithms python3 seq2seq unsupervised-learning distributed-representations latent-representations
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Apr 8, 2024 - Python
Variational Interpretable Concept Embeddings
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Dec 12, 2023 - Python
Code associated with the paper "Prior Image-Constrained Reconstruction using Style-Based Generative Models" accepted to ICML 2021.
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Jun 14, 2021 - Python
Simple Pytorch Implementation of BYOL: Bootstrap Your Own Latent(https://arxiv.org/abs/2006.07733) [Colab Version Available]
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May 17, 2021 - Jupyter Notebook
Official repository for the "Multiple wavefield solutions in physics-informed neural networks using latent representation" paper.
partial-differential-equations helmholtz-equation latent-representations physics-informed-neural-networks
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Nov 4, 2024 - Jupyter Notebook
A study on the effect of normalization in predictions by CNN models
deep-learning thesis uva artificial-intelligence classification convolutional-neural-networks variational-inference bias normalization bilateral-filter variational-autoencoder latent-representations shape-bias texture-bias
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Jul 4, 2019 - Jupyter Notebook
Latent-Explorer is the Python implementation of the framework proposed in the paper "Unveiling LLMs: The Evolution of Latent Representations in a Dynamic Knowledge Graph".
knowledge graphs knowledge-graph probing latent-representations factuality llms llms-reasoning propositional-probes claim-verification
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Oct 21, 2024 - Python
Investigate mapping of articulations from the image space to the latent space using neural networks.
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Nov 3, 2022 - Python
TensorFlow code and LaTex for Bachelor Thesis: Understanding Variational Autoencoders' Latent Representations of Remote Sensing Images 🌍
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May 17, 2021 - TeX
Working towards deliverable 5.3
journal paper biomarker-discovery latent-semantic-analysis stacked-denoising-autoencoders latent-representations
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Jul 4, 2021 - Python
📜 [MIDL 2022] "Sensor to Image Heterogeneous Domain Adaptation Network", Ishikaa Lunawat, Vignesh S, S P Sharan
deep-neural-networks pytorch domain-adaptation sensors-data-collection latent-representations vae-pytorch
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Oct 29, 2022 - Jupyter Notebook
Latent Representation and Exploration of Images Using Variational AutoEncoders
computer-vision deep-learning tensorflow image-processing vae variational-autoencoder latent-representations
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Feb 26, 2024 - Jupyter Notebook
This algorithm exploits the relationships between variables to improve the reconstruction performance of the variational autoencoder (VAE). A correlation score was used as the metric to group the features via a distance-based clustering method. The resulting clusters served as inputs for the Attention-Based VAE.
clustering attention-mechanism time-series-analysis variational-autoencoder dynamic-thresholding latent-representations
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Sep 14, 2024 - Python
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