agopal42

3d-shapes

This repository contains the 3D shapes dataset, used in Kim, Hyunjik and Mnih, Andriy. "Disentangling by Factorising." In Proceedings of the 35th International Conference on Machine Learning (ICML). 2018. to assess the disentanglement properties of unsupervised learning methods.

agopal42.github.io

repo for my personal webpage

atari-representation-learning

Code for "Unsupervised State Representation Learning in Atari"

complexPyTorch

A high-level toolbox for using complex valued neural networks in PyTorch

ctcae

Official code repository for NeurIPS 2023 paper "Contrastive Training of Complex-Valued Autoencoders for Object Discovery"

deepmind-research

This repository contains implementations and illustrative code to accompany DeepMind publications

disentanglement_lib

disentanglement_lib is an open-source library for research on learning disentangled representations.

permakey

Code repository complementing the ICLR 2021 paper "Unsupervised Object Keypoint Learning using Local Spatial Predictability" (https://arxiv.org/abs/2011.12930)

slottar

Code repository complementing the Neural Computation 2022 journal paper "Unsupervised Learning of Temporal Abstractions using Slot-based Transformers"

syncx

Official code repository for NeurIPS 2024 paper "Recurrent Complex-Weighted Autoencoders for Unsupervised Object Discovery"

agopal42/permakey

Code repository complementing the ICLR 2021 paper "Unsupervised Object Keypoint Learning using Local Spatial Predictability" (https://arxiv.org/abs/2011.12930)

agopal42/ctcae

Official code repository for NeurIPS 2023 paper "Contrastive Training of Complex-Valued Autoencoders for Object Discovery"

agopal42/slottar

Code repository complementing the Neural Computation 2022 journal paper "Unsupervised Learning of Temporal Abstractions using Slot-based Transformers"

agopal42/syncx

Official code repository for NeurIPS 2024 paper "Recurrent Complex-Weighted Autoencoders for Unsupervised Object Discovery"

agopal42/3d-shapes

This repository contains the 3D shapes dataset, used in Kim, Hyunjik and Mnih, Andriy. "Disentangling by Factorising." In Proceedings of the 35th International Conference on Machine Learning (ICML). 2018. to assess the disentanglement properties of unsupervised learning methods.

agopal42/agopal42.github.io

repo for my personal webpage

agopal42/atari-representation-learning

Code for "Unsupervised State Representation Learning in Atari"

agopal42/complexPyTorch

A high-level toolbox for using complex valued neural networks in PyTorch

agopal42/deepmind-research

This repository contains implementations and illustrative code to accompany DeepMind publications

agopal42/disentanglement_lib

disentanglement_lib is an open-source library for research on learning disentangled representations.

agopal42/einops

Deep learning operations reinvented (for pytorch, tensorflow, jax and others)

agopal42/ompn_craft

agopal42/rl-starter-files

RL starter files in order to immediatly train, visualize and evaluate an agent without writing any line of code