[NeurIPS 2020] Semi-Supervision (Unlabeled Data) & Self-Supervision Improve Class-Imbalanced / Long-Tailed Learning

This repository contains all the papers accepted in top conference of computer vision, with convenience to search related papers.

Fetch Academic Research Papers from different sources

Code for our NeurIPS 2022 paper

A PyTorch Implementation of "Watch Your Step: Learning Node Embeddings via Graph Attention" (NeurIPS 2018).

Code and Data artifact for NeurIPS 2023 paper - "Monitor-Guided Decoding of Code LMs with Static Analysis of Repository Context". `multispy` is a lsp client library in Python intended to be used to build applications around language servers.

[NeurIPS 2021] Galerkin Transformer: a linear attention without softmax for Partial Differential Equations

[NeurIPS'24] Generalizing Weather Forecast to Fine-grained Temporal Scales via Physics-AI Hybrid Modeling

multispy is a lsp client library in Python intended to be used to build applications around language servers.

Multi-Task Temporal Shift Attention Networks for On-Device Contactless Vitals Measurement (NeurIPS 2020)

[NeurIPS 2023] A Dynamics-informed Diffusion Model for Spatiotemporal Forecasting

Resources for the paper titled "EEG-GCNN: Augmenting Electroencephalogram-based Neurological Disease Diagnosis using a Domain-guided Graph Convolutional Neural Network". Accepted for publication (with an oral spotlight!) at ML4H Workshop, NeurIPS 2020.

Official PyTorch implementation of TSDiff models presented in the NeurIPS 2023 paper "Predict, Refine, Synthesize: Self-Guiding Diffusion Models for Probabilistic Time Series Forecasting"

This is our implementation of ENMF: Efficient Neural Matrix Factorization (TOIS. 38, 2020). This also provides a fair evaluation of existing state-of-the-art recommendation models.

Official implementation of CATs

[NeurIPS 2022 Spotlight] Expectation-Maximization Contrastive Learning for Compact Video-and-Language Representations

The code of NeurIPS 2021 paper "Scalable Rule-Based Representation Learning for Interpretable Classification" and TPAMI paper "Learning Interpretable Rules for Scalable Data Representation and Classification"

[NeurIPS 2023] Offical code for <Real3D-AD: A Dataset of Point Cloud Anomaly Detection>. A 3D point cloud anomaly detection dataset and benchmark.

🔥RayDF in PyTorch (NeurIPS 2023)

Optimal Sparse Decision Trees