Notes from Neurips 2019 Conference

Code accompanying the paper "Globally Optimal Learning for Structured Elliptical Losses", published at NeurIPS 2019

Private learning in NeurIPS 2019

Implementation of nested theory of mind belief estimation & implicit communication intrinsic rewards.

Python implementation of the Max-value Entropy Search for Multi-Objective Bayesian Optimization method

Review paper of neuropathic pain diagnosis(NeurIPS 2019) Implemented certain exercises more details in the pdf

My solution to the NeurIPS challenge Learn to Move: Walk Around

Tool for searching NeurIPS2019 proceedings

Implementation and supporting materials for the paper Multi-Criteria Dimensionality Reduction with Applications to Fairness, NeurIPS2019 and extend the prior work "The Price of Fair PCA: One Extra Dimension"

Python implementation of the Structured Graph Learning (SGL) algorithm by Kumar et. al (2019, https://papers.nips.cc/paper/9339-structured-graph-learning-via-laplacian-spectral-constraints)

Source code for "Mo′ States Mo′ Problems: Emergency Stop Mechanisms from Observation"

Submission name: QualcommAI-EfficientNet. MicroNet Challenge (NeurIPS 2019) submission - Qualcomm AI Research

Code for the paper: Foveated Convolutions: Improving Spatial Transformer Networks by Modelling the Retina

[NeurIPS 2019] Mobile-cloud split deep learning model inference

CellSignal (rxrx.ai) - NEURIPS 2019 COMPETITION

Code for 'Chasing Ghosts: Instruction Following as Bayesian State Tracking' published at NeurIPS 2019

3rd placed submission to the NeurIPS MineRL competition 2019

Pytorch based implementation of Upside Down Reinforcement Learning (UDRL) by J. Schmidhuber et al.

Code for the paper: Spatial and Colour Opponency in Anatomically Constrained Deep Networks