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Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
YOLOv10: Real-Time End-to-End Object Detection [NeurIPS 2024]
A Python implementation of global optimization with gaussian processes.
Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.
FILM: Frame Interpolation for Large Motion, In ECCV 2022.
Awesome machine learning for combinatorial optimization papers.
One repository is all that is necessary for Multi-agent Reinforcement Learning (MARL)
Riemannian Adaptive Optimization Methods with pytorch optim
Implementation of the Deep Deterministic Policy Gradient (DDPG) using PyTorch
A parallel framework for population-based multi-agent reinforcement learning.
Python library for CMA Evolution Strategy.
A performant NumPy extension for Galois fields and their applications
Open-source, state-of-the-art vehicle routing problem solver in an easy-to-use Python package.
A Pytorch implementation of the multi agent deep deterministic policy gradients (MADDPG) algorithm
Learn about particle swarm optimization (PSO) through Python!
Always sparse. Never dense. But never say never. A Sparse Training repository for the Adaptive Sparse Connectivity concept and its algorithmic instantiation, i.e. Sparse Evolutionary Training, to b…
[***JMLR-2024***] PyPop7: A Pure-Python Library for POPulation-based Black-Box Optimization (BBO), especially *Large-Scale* versions/variants (e.g., evolutionary algorithms, swarm-based optimizers,…
A Python 3 gradient-free optimization library
[CVPR 2024] Official implementation of "VRP-SAM: SAM with Visual Reference Prompt"
homura is a library for fast prototyping DL research
[NeurIPS 2020] Diversity-Guided Efficient Multi-Objective Optimization With Batch Evaluations
Adaptive Stochastic Natural Gradient Method for One-Shot Neural Architecture Search
The tree-structured Parzen estimator (TPE) implementation and the simple running code for it
A simple PyTorch implementation of Population Based Training of Neural Networks.
PyTorch implementation of FIM and empirical FIM