dblanm
Researcher @ IRI-CSIC-UPC | Visiting PhD Candidate @ Aalto University. Learning for manipulation, deformable objects and reinforcement learning.
Institut de Robòtica i Informàtica IndustrialBarcelona, Spain
dblanm's Stars
deepmind/deepmind-research
This repository contains implementations and illustrative code to accompany DeepMind publications
aikorea/awesome-rl
Reinforcement learning resources curated
HIPS/autograd
Efficiently computes derivatives of NumPy code.
naganandy/graph-based-deep-learning-literature
links to conference publications in graph-based deep learning
DLR-RM/BlenderProc
A procedural Blender pipeline for photorealistic training image generation
sofa-framework/sofa
Real-time multi-physics simulation with an emphasis on medical simulation.
WilsonWangTHU/mbbl
sympy/sympy.github.com
SymPy's web page (sympy.org)
petrikvladimir/pyphysx
Python Wrapper for Nvidia PhysX simulator.
markvdw/convgp
Convolutional Gaussian processes based on GPflow.
AaltoML/kalman-jax
Approximate inference for Markov Gaussian processes using iterated Kalman smoothing, in JAX
williamljb/DifferentiableCloth
contactrika/dedo
Dynamic Environments with Deformable Objects (DEDO)
fabriziocosta/EDeN
Explicit Decomposition with Neighborhoods python version
DanielTakeshi/gym-cloth
Code for IROS 2020 paper: https://arxiv.org/abs/1910.04854
columbia-ai-robotics/dextairity
[RSS 2022, Best System Paper Finalist] DextAIRity: Deformable Manipulation Can be a Breeze
aboustati/dgplib
Library for Deep Gaussian Processes based on GPflow
edlanglois/mbbl-pilco
Implementation of PILCO for the Model-Based Baselines Project
maxbren/Reinforcement-Learning-Papers-Notes
Notes on many interesting RL papers
Victorlouisdg/differentiable-cloth-folding
Cloth Folding Through Differentiable Physcis Simulation
nips20-2515/DGP-Graph
Codes for paper "Stochastic Deep Gaussian Processes over Graphs"
dinhinfotech/Conjuncitve_Disjunctive_Kernel
This is the test repository in github
dinhinfotech/Deepwl
wunan3/Diffusion-based-Gaussian-Process
hietalajulius/gym
A toolkit for developing and comparing reinforcement learning algorithms.