LeizhenWang's Stars
bayesian-optimization/BayesianOptimization
A Python implementation of global optimization with gaussian processes.
datawhalechina/hugging-llm
HuggingLLM, Hugging Future.
cvxgrp/cvxpylayers
Differentiable convex optimization layers
Thinklab-SJTU/awesome-ml4co
Awesome machine learning for combinatorial optimization papers.
DiffEqML/torchdyn
A PyTorch library entirely dedicated to neural differential equations, implicit models and related numerical methods
datawhalechina/hugging-multi-agent
A tutorial based on MetaGPT to quickly help you understand the concept of agent and muti-agent and get started with coding development. 基于MetaGPT的多智能体入门与开发教程
bayesoptbook/bayesoptbook.github.io
Companion webpage for the book "Bayesian Optimization" by Roman Garnett
altdeep/causalML
The open source repository for the Causal Modeling in Machine Learning Workshop at Altdeep.ai @ www.altdeep.ai/courses/causalML
khalil-research/PyEPO
A PyTorch-based End-to-End Predict-then-Optimize Library for Linear and Integer Programming
boschresearch/torchphysics
locuslab/mdeq
[NeurIPS'20] Multiscale Deep Equilibrium Models
PointsCoder/GPT-Driver
Learning to Drive with GPT
locuslab/deq-flow
[CVPR 2022] Deep Equilibrium Optical Flow Estimation
usail-hkust/LLMTSCS
Official code for article "LLMLight: Large Language Models as Traffic Signal Control Agents".
boschresearch/multiplicative-filter-networks
Source code for Fathony, Sahu, Willmott, & Kolter, "Multiplicative Filter Networks", ICLR 2021.
locuslab/torchdeq
Modern Fixed Point Systems using Pytorch
KrisNguyen135/bayesian-optimization-in-action
Source code for Bayesian Optimization in Action, published by Manning
Chrisejorge/Causal-Inference
Materials Collection for Causal Inference
facebookresearch/neural-scs
Neural Fixed-Point Acceleration for Convex Optimization
DaRL-LibSignal/PromptGAT
PromptGAT: Prompt learning for Sim2Real under reinforcement learning
arjhuang/pise
Physics Informed Deep Learning for Traffic State Estimation: Illustrations with LWR and CTM Models
pabloguarda/pesuelogit
Parameter Estimation of LOGIT-based Stochastic User Equilibrium models using computational graphs and day-to-day system-level data
pabloguarda/probabilistic-graphical-transportation-networks
Probabilistic graphical models to learn Origin-Destination matrices in transportation networks using TensorFlow
stellatogrp/learning_rationality_in_potential_games
ArbeitsgruppeTobiasHarks/dynamic-prediction-equilibria
Computation of dynamic selfish flows using predicted travel times
khalil-research/Neur2BiLO
pabloguarda/mate
Network-wide estimation of traffic flow and travel time with data-driven macroscopic models
pabloguarda/neural-transportation-networks
Data-driven neural models to learn and predict travel behavior in transportation networks using PyTorch
DanielMckenzie/Nash_FPNs
Nash FPNs: Learning to Predict Nash equilibria from data using implicit neural networks
Zero8319/DACOOP-A