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GeoCalib: Learning Single-image Calibration with Geometric Optimization (ECCV 2024)
A library for scientific machine learning and physics-informed learning
Release repo for our SLAM Handbook
PyTorch Implementation of Physics-informed Neural Networks
Solve forward and inverse problems related to partial differential equations using finite basis physics-informed neural networks (FBPINNs)
High throughput synchronous and asynchronous reinforcement learning
Generative Pre-Trained Physics-Informed Neural Networks Implementation
Implementation of stable-baselines3 in rust with burn
Use PyTorch Models with CasADi for data-driven optimization or learning-based optimal control. Supports Acados.
An efficient pure-PyTorch implementation of Kolmogorov-Arnold Network (KAN).
A steerer for D-dimensional keypoint descriptions is a DxD matrix that transforms the descriptions as if they were computed from a rotated image.
DeepONets, (Fourier) Neural Operators, Physics-Informed Neural Operators, and more in Julia
Optimization-Based Collision Avoidance - a path planner for autonomous navigation
DORA (Dataflow-Oriented Robotic Architecture) is middleware designed to streamline and simplify the creation of AI-based robotic applications. It offers low latency, composable, and distributed dat…
Schedule-Free Optimization in PyTorch
A grid world environment for high-level earthworks planning in JAX for RL.
Codebase for PINNacle: A Comprehensive Benchmark of Physics-Informed Neural Networks for Solving PDEs.
stereo rectification and stereo matching for perspective camera and fisheye camera, based on opencv
Dynamical movement primitives (DMPs), probabilistic movement primitives (ProMPs), and spatially coupled bimanual DMPs for imitation learning.
Funktional generic type-level programming in Rust: HList, Coproduct, Generic, LabelledGeneric, Validated, Monoid and friends.
