Samip Dahal (sdpmas)

sdpmas

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Location:Chapel Hill, NC

Home Page:https://sdpmas.github.io/

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Samip Dahal's starred repositories

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Awesome-GFlowNets

A curated list of resources about generative flow networks (GFlowNets).

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dreamerv3

Mastering Diverse Domains through World Models

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information-bottleneck

Deep Learning & Information Bottleneck

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HEPML-LivingReview

Living Review of Machine Learning for Particle Physics

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hivemind

Decentralized deep learning in PyTorch. Built to train models on thousands of volunteers across the world.

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category-theory-resources

Resources for learning Category Theory for an enthusiast

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LAVIS

LAVIS - A One-stop Library for Language-Vision Intelligence

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raspy

An interactive exploration of Transformer programming.

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Megatron-LM

Ongoing research training transformer models at scale

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CatGNN

Prototype for a Category Theory-based GNN Library

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TNP-pytorch

Official implementation of Transformer Neural Processes

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gflownet

Generative Flow Networks

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lila

Code for "Invariance Learning in Deep Neural Networks with Differentiable Laplace Approximations"

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GNCA

Code for "Learning Graph Cellular Automata" (NeurIPS 2021).

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G.pt

Official PyTorch Implementation of "Learning to Learn with Generative Models of Neural Network Checkpoints"

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iris

Transformers are Sample-Efficient World Models. ICLR 2023, notable top 5%.

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neural-network-cuda

A neural network from scratch in CUDA/C++

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torchsort

Fast, differentiable sorting and ranking in PyTorch

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torchdiffeq

Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.

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triton

Development repository for the Triton language and compiler

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ml-compiler-opt

Infrastructure for Machine Learning Guided Optimization (MLGO) in LLVM.

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einops

Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others)

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minimal-flask-api

A template for 'production ready' Flask APIs with Flask & Gunicorn. Includes template test and error-handling files.

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bolt

10x faster matrix and vector operations

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cuda_programming

Code from the "CUDA Crash Course" YouTube series by CoffeeBeforeArch

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lvt

The PyTorch implementation of Latent Video Transformer.

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