Stars
Open-source Multi-agent Poster Generation from Papers
Sample implementation of Neural Ordinary Differential Equations
HyPro: A C++ state set representation library for the analysis of hybrid systems
Graph neural ordinary differential equations
ROS2 package implementing an interface for the Stonefish library.
ROS package implementing an interface for the Stonefish library.
A library for solving differential equations using neural networks based on PyTorch, used by multiple research groups around the world, including at Harvard IACS.
Verification of Continuous Time Recurrent Neural Networks (CTRNN)
Official implementation of "The Sparse Frontier: Sparse Attention Trade-offs in Transformer LLMs"
This introduces a suggestion of mathematical notation protocol for machine learning.
mkhaled87 / pFaces-PIRK
Forked from alexdevonport/pfaces-pirkA tool for parallel computation of interval over-approximations to reachable sets of nonlinear control systems, powered by the pFaces acceleration ecosystem; more briefly, a Parallel Interval Reach…
Visualizer for neural network, deep learning and machine learning models
Open-source combined Linear Algebra and Ordinary Differential Equations textbook
A Survey on the Honesty of Large Language Models
Constrained deep learning is an advanced approach to training deep neural networks by incorporating domain-specific constraints into the learning process.
Jupyter notebook with Pytorch implementation of Neural Ordinary Differential Equations
High performance ordinary differential equation (ODE) and differential-algebraic equation (DAE) solvers, including neural ordinary differential equations (neural ODEs) and scientific machine learni…
nosnoc is an open source software package for NOnSmooth Numerical Optimal Control.
A Python package for probabilistic state space modeling with JAX
Fair-code workflow automation platform with native AI capabilities. Combine visual building with custom code, self-host or cloud, 400+ integrations.
PlanDQ: Hierarchical Plan Orchestration via D-Conductor and Q-Performer
Formal Verification of Neural Feedback Loops (NFLs)
Literature survey, paper reviews, experimental setups and a collection of implementations for baselines methods for predictive uncertainty estimation in deep learning models.