Improved GQ-CNN: Deep Learning Model for Planning Robust Grasps

no code implementations • 16 Feb 2018 • Maciej Jaśkowski, Jakub Świątkowski, Michał Zając, Maciej Klimek, Jarek Potiuk, Piotr Rybicki, Piotr Polatowski, Przemysław Walczyk, Kacper Nowicki, Marek Cygan

In this work we improve on one of the most promising approaches, the Grasp Quality Convolutional Neural Network (GQ-CNN) trained on the DexNet 2. 0 dataset.

On the Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks

no code implementations • 25 Sep 2019 • Jakub Świątkowski, Kevin Roth, Bastiaan S. Veeling, Linh Tran, Joshua V. Dillon, Jasper Snoek, Stephan Mandt, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin

Variational Bayesian Inference is a popular methodology for approximating posterior distributions in Bayesian neural networks.

Bayesian Inference Variational Inference

How Good is the Bayes Posterior in Deep Neural Networks Really?

1 code implementation • ICML 2020 • Florian Wenzel, Kevin Roth, Bastiaan S. Veeling, Jakub Świątkowski, Linh Tran, Stephan Mandt, Jasper Snoek, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin

In this work we cast doubt on the current understanding of Bayes posteriors in popular deep neural networks: we demonstrate through careful MCMC sampling that the posterior predictive induced by the Bayes posterior yields systematically worse predictions compared to simpler methods including point estimates obtained from SGD.

Bayesian Inference Uncertainty Quantification

Continuous Control With Ensemble Deep Deterministic Policy Gradients

1 code implementation • 30 Nov 2021 • Piotr Januszewski, Mateusz Olko, Michał Królikowski, Jakub Świątkowski, Marcin Andrychowicz, Łukasz Kuciński, Piotr Miłoś

The growth of deep reinforcement learning (RL) has brought multiple exciting tools and methods to the field.

Continuous Control OpenAI Gym +2