Piyushi-0

ACE

Code for our ICML '19 paper: Neural Network Attributions: A Causal Perspective.

Fair-MAMAB

Code for our AAMAS '25 paper, 'Multi-agent Multi-armed Bandits with Minimum Reward Guarantee Fairness'.

LessIsMoreICLR24

[ICLR 2024 Oral] Less is More: Fewer Interpretable Region via Submodular Subset Selection

MMD-reg-OT

Code for our TMLR '24 Journal: MMD-Regularized UOT.

my-understanding-of-ML-Theory

OTAlign

Repository of ACL2023 paper: Unbalanced Optimal Transport for Unbalanced Word Alignment

sampling_diffusion

Improved sampling via learned diffusions (ICLR2024) and an optimal control perspective on diffusion-based generative modeling (SBM@NeurIPS2022)

SEA-NN

Code for our AISTATS '22 paper: Improving Attribution Methods by Learning Submodular Functions.

Sparse-UOT

Code for our ICML '24 paper, "Submodular framework for structured-sparse optimal transport".

w2ot

Euclidean Wasserstein-2 optimal transportation

Piyushi-0/ACE

Code for our ICML '19 paper: Neural Network Attributions: A Causal Perspective.

Piyushi-0/agglio

Accelerated Graduated Generalized Linear-model Optimization

Piyushi-0/COOT

CO-Optimal Transport

Piyushi-0/copt

[NeurIPS 2020]. COPT - Coordinated Optimal Transport on Graphs

Piyushi-0/cs228-notes

Course notes for CS228: Probabilistic Graphical Models.

Piyushi-0/GDL

Code for Online Graph Dictionary Learning

Piyushi-0/H-Divergence

Piyushi-0/JUMBOT

Official Python3 implementation of our ICML 2021 paper "Unbalanced minibatch Optimal Transport; applications to Domain Adaptation"

Piyushi-0/My_codes-Misc

Some of my codes.

Piyushi-0/DCFR

Source code for KDD 2020 paper "Algorithmic Decision Making with Conditional Fairness".

Piyushi-0/disentanglement

Official repository for our ICLR 2021 paper Evaluating the Disentanglement of Deep Generative Models with Manifold Topology

Piyushi-0/ICLR2020-CFair

Piyushi-0/LP-DeepSSL

Code for CVPR 2019 paper Label Propagation for Deep Semi-supervised Learning

Piyushi-0/mars_domain_adaptation

Piyushi-0/msda-moe

Code and data for the paper "Multi-Source Domain Adaptation with Mixture of Experts" (EMNLP 2018)

Piyushi-0/NLP_Projects

A collection of projects built using PyTorch & NLTK implementing Deep Learning Models for NLP-related tasks

Piyushi-0/NTK-MMD

Neural Tangent Kernel MMD

Piyushi-0/old-codes

Piyushi-0/OT-Seq2Seq-PyTorch

an unofficial PyTorch implementation of ICLR 2019 paper IMPROVING SEQUENCE-TO-SEQUENCE LEARNING VIA OPTIMAL TRANSPORT

Piyushi-0/OTK

A Pytorch implementation of the optimal transport kernel embedding

Piyushi-0/private-data-generation

A toolbox for differentially private data generation

Piyushi-0/pytorch-mixture-of-experts

using deepspeed to build a distributed mixture of experts model

Piyushi-0/Regularization-Pruning

[ICLR'21] Neural Pruning via Growing Regularization (PyTorch)

Piyushi-0/SCOT

CVPR 2020, Semantic Correspondence as an Optimal Transport Problem, Pytorch Implementation.

Piyushi-0/smooth-ot

Python implementation of smooth optimal transport.

Piyushi-0/SWAE

Code for Symmetric Wasserstein Autoencoders (UAI 2021)

Piyushi-0/trVAE

Conditional out-of-distribution prediction

Piyushi-0/trvaep

Piyushi-0/TVS_Prune

TVS Prune source code. Includes pruning scripts and ipython notebooks for plotting figures. Requires >16GB RAM.

Piyushi-0/visual-attribution

Pytorch Implementation of recent visual attribution methods for model interpretability