celik02
PhD Candidate in Systems Engineering - Robotics, Control, and Deep Learning
Boston University Boston,MA
celik02's Stars
facebookresearch/pytorch3d
PyTorch3D is FAIR's library of reusable components for deep learning with 3D data
NVIDIA/flownet2-pytorch
Pytorch implementation of FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks
princeton-vl/RAFT
tomrunia/OpticalFlow_Visualization
Python optical flow visualization following Baker et al. (ICCV 2007) as used by the MPI-Sintel challenge
changhao-chen/selective_sensor_fusion
Webpage for Selective Sensor Fusion
Lightning-AI/pytorch-lightning
Pretrain, finetune ANY AI model of ANY size on multiple GPUs, TPUs with zero code changes.
facebookresearch/segment-anything
The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.
shikharbahl/neural-dynamic-policies
zh320/realtime-semantic-segmentation-pytorch
PyTorch implementation of over 30 realtime semantic segmentations models, e.g. BiSeNetv1, BiSeNetv2, CGNet, ContextNet, DABNet, DDRNet, EDANet, ENet, ERFNet, ESPNet, ESPNetv2, FastSCNN, ICNet, LEDNet, LinkNet, PP-LiteSeg, SegNet, ShelfNet, STDC, SwiftNet, and support knowledge distillation, distributed training, Optuna etc.
shaoanlu/mppi_cbf
Colab notebooks showcasing experiments on MPPI (model predictive path integral control) and CBF (control barrier function). Utilizes jax to accelerate computation.
zhejz/carla-roach
Roach: End-to-End Urban Driving by Imitating a Reinforcement Learning Coach. ICCV 2021.
locuslab/icnn
Input Convex Neural Networks
OpenDriveLab/TCP
[NeurIPS 2022] Trajectory-guided Control Prediction for End-to-end Autonomous Driving: A Simple yet Strong Baseline.
opendilab/InterFuser
[CoRL 2022] InterFuser: Safety-Enhanced Autonomous Driving Using Interpretable Sensor Fusion Transformer
All-Hands-AI/OpenHands
🙌 OpenHands: Code Less, Make More
wanxinjin/Safe-PDP
Safe Pontryagin Differentiable Programming (Safe PDP) is a new theoretical and algorithmic safe differentiable framework to solve a broad class of safety-critical learning and control tasks.
wanxinjin/Pontryagin-Differentiable-Programming
A unified end-to-end learning and control framework that is able to learn a (neural) control objective function, dynamics equation, control policy, or/and optimal trajectory in a control system.
shantanu-ai/deep-learning-resources
Resources needed to start deep learning research. ML/DL/CV/NLP/ML-SYS/RL/Graphs/Maths/Med image lecture videos from professors at esteemed universities.
greydanus/hamiltonian-nn
Code for our paper "Hamiltonian Neural Networks"
mingu6/Implicit-Diff-Optimal-Control
Reference implementation for the paper "Revisiting Implicit Differentiation for Learning Problems in Optimal Control" (NeurIPS 2023).
bu-rcs/Intro_to_SCC
Introduction to the Shared Computing Cluster
autonomousvision/carla_garage
[ICCV'23] Hidden Biases of End-to-End Driving Models
locuslab/qpth
A fast and differentiable QP solver for PyTorch.
locuslab/mpc.pytorch
A fast and differentiable model predictive control (MPC) solver for PyTorch.
AIHawk-FOSS/Auto_Jobs_Applier_AI_Agent
Auto_Jobs_Applier_AI_Agent by AIHawk is an AI Agent that automates the jobs application process. Utilizing artificial intelligence, it enables users to apply for multiple jobs in an automated and personalized way.
lukas-blecher/LaTeX-OCR
pix2tex: Using a ViT to convert images of equations into LaTeX code.
chaveza9/LearningSafety
facebookresearch/theseus
A library for differentiable nonlinear optimization
cisimon7/VQOptMain
Tim-Salzmann/l4casadi
Use PyTorch Models with CasADi for data-driven optimization or learning-based optimal control. Supports Acados.