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[NeurIPS 2026] World from Motion: Generative Dynamic Gaussian Reconstruction from Monocular Videos

A Python toolbox for performing gradient-free optimization

Distributed GPU-Accelerated Framework for Evolutionary Computation. Comprehensive Library of Evolutionary Algorithms & Benchmark Problems.

google-deepmind / optax

Optax is a gradient processing and optimization library for JAX.

kengz / SLM-Lab

Modular Deep Reinforcement Learning framework in PyTorch. Companion library of the book "Foundations of Deep Reinforcement Learning".

AlexanderVanhee / Gradia

Make your screenshots ready for all

GradientHQ / symphony-coord

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fangvv / UAV-DDPG

Code for paper "Computation Offloading Optimization for UAV-assisted Mobile Edge Computing: A Deep Deterministic Policy Gradient Approach"

simpeg / simpeg

Simulation and Parameter Estimation in Geophysics - A python package for simulation and gradient based parameter estimation in the context of geophysical applications.

johnmarktaylor91 / torchlens

Capture every activation and gradient of any PyTorch model — forward and backward — with automatic graph visualization, rich metadata, and live interventions. Works on any architecture, including dynamic and recurrent ones.

iit-DLSLab / Quadruped-PyMPC

A model predictive controller for quadruped robots based on the single rigid body model and written in python. Gradient-based (acados) or Sampling-based (jax)

Zihan-Su / Self_Gradient_Forcing_Plus

Autoregressive video generation with decoupled context-writing and denoising parameters, enabling up to 24-hour generation from 5s training windows.

Birfy / agentdescent

Gradient descent, but the parameters are agents — a parallel, asynchronous framework for self-evolving agents (skills, prompts, harnesses). Diffs are the gradients; the aggregator is the optimizer.

zhuang2002 / Self_Gradient_Forcing

Self Gradient Forcing (SGF) recovers the missing context-gradient path for self-generated causal memory through a bounded two-pass replay, enabling models trained with only a 5-second window to extrapolate to minute-scale videos with stronger identity, layout, and temporal stability.

yfyeung / PrunedCTC

Memory-efficient CTC loss with exact loss and first-order gradient equivalence under vocabulary reduction, and activation memory that no longer scales linearly with vocabulary size.

Belucking / GradientMempool

A simple GradientMempool Engine for Network Congestion Mitigation.

Optima-CityU / neural-spectral-capacity

NSC measures neural architecture capacity directly from network specifications, without data, gradients, or model instantiation. Its additive structure enables exact architecture optimization under resource budgets in seconds on a CPU.