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Transforms your CasADi functions into batchable JAX-compatible functions. By combining the power of CasADi with the flexibility of JAX, JAXADi enables the creation of efficient code that runs smoot…
An Extensible Benchmarking Platform for Scalable Dynamical System Identification
tsl: a PyTorch library for processing spatiotemporal data.
Code for "SINDy-RL: Interpretable and Efficient Model-Based Reinforcement Learning" by Zolman et al.
Supplementary Material "Co-Design Optimisation of Morphing Topology and Control of Winged Drones" published in IEEE 2024 International Conference on Robotics and Automation (ICRA)
Physics-informed Machine Learning for Modeling, Control, and Optimization at CDC 2024
Pretrain, finetune and deploy AI models on multiple GPUs, TPUs with zero code changes.
Optax is a gradient processing and optimization library for JAX.
"Deep Generative Modeling": Introductory Examples
Productive, portable, and performant GPU programming in Python.
10 differentiable physical simulators built with Taichi differentiable programming (DiffTaichi, ICLR 2020)
BackPACK - a backpropagation package built on top of PyTorch which efficiently computes quantities other than the gradient.
A Production-ready Reinforcement Learning AI Agent Library brought by the Applied Reinforcement Learning team at Meta.
A reactive notebook for Python — run reproducible experiments, execute as a script, deploy as an app, and version with git.
An experimental language for causal reasoning
Learning to Optimize with Proximal Operators (LOPO)
A flexible package manager that supports multiple versions, configurations, platforms, and compilers.
Physics Informed Machine Learning Tutorials (Pytorch and Jax)
⚡ Dynamically generated stats for your github readmes
A beautiful, simple, clean, and responsive Jekyll theme for academics
Mathematical Optimization in Julia. Local, global, gradient-based and derivative-free. Linear, Quadratic, Convex, Mixed-Integer, and Nonlinear Optimization in one simple, fast, and differentiable i…
PDEBench: An Extensive Benchmark for Scientific Machine Learning
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.