Popular GitHub Repositories for Physical Constraints

AI constraint solver in Java to optimize the vehicle routing problem, employee rostering, task assignment, maintenance scheduling, conference scheduling and other planning problems.

An open-source data logging library for machine learning models and data pipelines. ? Provides visibility into data quality & model performance over time. ?️ Supports privacy-preserving data collection, ensuring safety & robustness. ?

Code implementation of "Learning Efficient Online 3D Bin Packing on Packing Configuration Trees". We propose to enhance the practical applicability of online 3D Bin Packing Problem (BPP) via learning on a hierarchical packing configuration tree which makes the deep reinforcement learning (DRL) model easy to deal with practical constraints and well-performing even with continuous solution space.

Implementation of π?, the robotic foundation model architecture proposed by Physical Intelligence

Gokart solves reproducibility, task dependencies, constraints of good code, and ease of use for Machine Learning Pipeline.

A Compositional Object-Based Approach to Learning Physical Dynamics

A toolkit for non-parallel voice conversion based on vector-quantized variational autoencoder

Physical adversarial attack for fooling the Faster R-CNN object detector

Transformers for modeling physical systems

[CVPRW 2024]Official PyTorch Implementation of "LAformer: Trajectory Prediction for Autonomous Driving with Lane-Aware Scene Constraints"

Neural Network Verification Software Tool

Controlled text generation with programmable constraints.

An Integrated Cyber-Physical Ecosystem for Autonomous Driving Research and Education

[ACL 2024] FollowBench: A Multi-level Fine-grained Constraints Following Benchmark for Large Language Models

Code for the paper "Thermodynamics-informed graph neural networks" published in IEEE Transactions on Artificial Intelligence (TAI).

Erwin: A Tree-based Hierarchical Transformer for Large-scale Physical Systems

Simulating Large-Scale Multi-Agent Interactions with Limited Multimodal Senses and Physical Needs

Unsupervised learning of atomic scale dynamics from molecular dynamics.

[CVPR 2024] Physical Property Understanding from Language-Embedded Feature Fields

[CVPR'24] Validation-free few-shot adaptation of CLIP, using a well-initialized Linear Probe (ZSLP) and class-adaptive constraints (CLAP).