Iterative Linear Quadratic Regulator with auto-differentiatiable dynamics models
- trajectory-optimization
- differential-dynamic-programming
- theano
- dynamics-models
Repository Index
47,133 repositories indexed
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GEARS is a geometric deep learning model that predicts outcomes of novel multi-gene perturbations
Make Gemini code like Claude Models. Forces it to inspect files before editing, plan changes, test its work, and back up every “done” with actual evidence.
- agent-skills
- antigravity-skills
- gemini
- prompt-engineering
Real-time generative rendering for interactive worlds, from any visual reference.
- game
- renderer
- video-generation
- game-engine
Naive-N0.5-Flash is an open-weight 309B MoE model with 15.5B active parameters, built for coding and AI R&D.
News reader with tags, scoring, and LLM
- feed
- feed-aggregator
- feed-reader
- news
Hyperparameter optimization and feature selection for scikit-learn using evolutionary algorithms. A modern alternative to GridSearchCV and RandomizedSearchCV.
Lightweight Claude Code statusLine: 5h/7d rate-limit usage, reset countdowns, model + context window, prompt-cache age — one line, 3 styles × 9 themes, daemon fast-mode
Reproduction of SuperMimic (arXiv:2610.28480): learned differentiable world model + BPTT policy for G1 humanoid motion tracking, on mjlab/MuJoCo Warp
Pathology Language and Image Pre-Training (PLIP) is the first vision and language foundation model for Pathology AI (Nature Medicine). PLIP is a large-scale pre-trained model that can be used to extract visual and language features from pathology images and text description. The model is a fine-tuned version of the original CLIP model.
- artificial-intelligence
- clip
- pathology
- vision-and-language
The first open-source model for code-driven video creation.
The repository host gives no description.
- auditing-predictive-models
- fairness
- discrimination
- toolbox
PyStan, a Python interface to Stan, a platform for statistical modeling. Documentation: https://pystan.readthedocs.io
Model extraction attacks on Machine-Learning-as-a-Service platforms.
NNDial is an open source toolkit for building end-to-end trainable task-oriented dialogue models. It is released by Tsung-Hsien (Shawn) Wen from Cambridge Dialogue Systems Group under Apache License 2.0.
- machine-learning
- dialogue-systems
- dialogue-generation
- dialogues
The official implementation of 3D Equivariant Diffusion for Target-Aware Molecule Generation and Affinity Prediction (ICLR 2023)
- ai-for-science
- diffusion-models
- drug-design
- equivariant-networks
UCE is a zero-shot foundation model for single-cell gene expression data
AgML is a centralized framework for agricultural machine learning. AgML provides access to public agricultural datasets for common agricultural deep learning tasks, with standard benchmarks and pretrained models, as well the ability to generate synthetic data and annotations.
- deep-learning
- agriculture
- pytorch
- dataset
pyMOR - Model Order Reduction with Python
- python
- model-reduction
- model-order-reduction
- control-systems
A unified framework for tabular probabilistic regression, time-to-event prediction, and probability distributions in python
- python
- sklearn
- data-science
- framework
OPAL: a reactive optimizer. A coding agent rewrites the optimizer while your model trains.
- deep-learning
- llm-agents
- optimizer
- pytorch
[arXiv 2026] Unified Audio-Video Creation via Progressive Training and Asymmetric Scheduling
- audio-to-video
- joint-audio-video-generation
- unified-model
- video-to-audio
Python parser for URDFs
- ros
- urdf-visualizer
- urdf-descriptions
- urdf-models
A 4B grounding foundation model for physical intelligence. Unifies detection, referring, pointing, OCR, GUI, and layout grounding, achieving SOTA overall across 34 benchmarks and improving robot generalization and data efficiency in controlled evaluations.
- embodied-ai
- gui-grounding
- object-detection
- ocr