Pinned Repositories
ao
torchao: PyTorch Architecture Optimization (AO). A repository to host AO techniques and performant kernels that work with PyTorch.
awesome-deep-gnn
Papers about developing deep Graph Neural Networks (GNNs)
Awesome-Efficient-LLM
A curated list for Efficient Large Language Models
awesome-explainable-graph-reasoning
A collection of research papers and software related to explainability in graph machine learning.
Awesome-Pruning
A curated list of neural network pruning resources.
RWL-GNN
Official pytorch code for "RWL-GNN: Robustifying Graph Neural Networks via Weighted Laplacian" (SPCOM 2022)
DEFT
Official pytorch code for "From PEFT to DEFT: Parameter Efficient Finetuning for Reducing Activation Density in Transformers"
Progressive-Pruning
Official pytorch code for "APP: Anytime Progressive Pruning" (DyNN @ ICML, 2022; CLL @ ACML, 2022, SNN @ ICML, 2022 and SlowDNN 2023)
taskgen
Task-based Agentic Framework using StrictJSON as the core
reduce_reuse_recycle
ICML 2023: Reduce, Reuse, Recycle: Composing Energy-Based Diffusion Models with MCMC
Bharat-Runwal's Repositories
Bharat-Runwal/counter-fitting
Counter-fitting Word Vectors to Linguistic Constraints
Bharat-Runwal/Data-Structures-and-Algorithms
Bharat-Runwal/Deep-learning
It contains implementation of deep learning projects.
Bharat-Runwal/exploring_t5
Bharat-Runwal/FLAG
Adversarial Data Augmentation for Graph Neural Networks.
Bharat-Runwal/Hackathon
Bharat-Runwal/Image-Steganography-using-lsb
Involves embedding a secret message in an image
Bharat-Runwal/Kaggle
Bharat-Runwal/Machine-Learning
Bharat-Runwal/Paper-Reading
Bharat-Runwal/path2vec
Learning to represent shortest paths and other graph-based measures of node similarities with graph embeddings
Bharat-Runwal/pyconv
Pyramidal Convolution: Rethinking Convolutional Neural Networks for Visual Recognition (https://arxiv.org/pdf/2006.11538.pdf)
Bharat-Runwal/RL
Bharat-Runwal/ro_sgns
Implementation of Riemannian optimization for skip-gram negative sampling (ACL 2017)
Bharat-Runwal/spectralGraphTopology
Learning Graphs from Data via Spectral Constraints for k-component, bipartite, and k-component bipartite graphs