Manuel Wüthrich | DeepAI

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∙ 09/03/2023

Generative Social Choice

Traditionally, social choice theory has only been applicable to choices ...

0 Sara Fish, et al. ∙

∙ 08/15/2023

Real Robot Challenge 2022: Learning Dexterous Manipulation from Offline Data in the Real World

Experimentation on real robots is demanding in terms of time and costs. ...

0 Nico Gürtler, et al. ∙

∙ 07/28/2023

Benchmarking Offline Reinforcement Learning on Real-Robot Hardware

Learning policies from previously recorded data is a promising direction...

0 Nico Gürtler, et al. ∙

∙ 03/06/2023

Optimal Engagement-Diversity Tradeoffs in Social Media

Social media platforms are known to optimize user engagement with the he...

0 Fabian Baumann, et al. ∙

∙ 02/27/2023

Eliciting Information from participants with Competing Incentives and Dependent Beliefs

In this paper, we study belief elicitation about an uncertain future eve...

0 Manuel Wüthrich, et al. ∙

∙ 11/28/2022

Representation with Incomplete Votes

Platforms for online civic participation rely heavily on methods for con...

0 Daniel Halpern, et al. ∙

∙ 05/19/2022

Dexterous Robotic Manipulation using Deep Reinforcement Learning and Knowledge Transfer for Complex Sparse Reward-based Tasks

This paper describes a deep reinforcement learning (DRL) approach that w...

5 Qiang Wang, et al. ∙

∙ 08/22/2021

Transferring Dexterous Manipulation from GPU Simulation to a Remote Real-World TriFinger

We present a system for learning a challenging dexterous manipulation ta...

3 Arthur Allshire, et al. ∙

∙ 07/12/2021

Representation Learning for Out-Of-Distribution Generalization in Reinforcement Learning

Learning data representations that are useful for various downstream tas...

48 Andrea Dittadi, et al. ∙

∙ 04/29/2021

Regret Bounds for Gaussian-Process Optimization in Large Domains

The goal of this paper is to characterize Gaussian-Process optimization ...

11 Manuel Wüthrich, et al. ∙

∙ 10/27/2020

On the Transfer of Disentangled Representations in Realistic Settings

Learning meaningful representations that disentangle the underlying stru...

24 Andrea Dittadi, et al. ∙

∙ 10/14/2020

Function Contrastive Learning of Transferable Representations

Few-shot-learning seeks to find models that are capable of fast-adaptati...

8 Muhammad Waleed Gondal, et al. ∙

∙ 10/08/2020

CausalWorld: A Robotic Manipulation Benchmark for Causal Structure and Transfer Learning

Despite recent successes of reinforcement learning (RL), it remains a ch...

5 Ossama Ahmed, et al. ∙

∙ 08/08/2020

TriFinger: An Open-Source Robot for Learning Dexterity

Dexterous object manipulation remains an open problem in robotics, despi...

2 Manuel Wüthrich, et al. ∙

∙ 07/13/2020

S2RMs: Spatially Structured Recurrent Modules

Capturing the structure of a data-generating process by means of appropr...

5 Nasim Rahaman, et al. ∙

∙ 09/30/2019

An Open Torque-Controlled Modular Robot Architecture for Legged Locomotion Research

We present a new open-source torque-controlled legged robot system, with...

0 Felix Grimminger, et al. ∙

∙ 06/07/2019

On the Transfer of Inductive Bias from Simulation to the Real World: a New Disentanglement Dataset

Learning meaningful and compact representations with structurally disent...

4 Muhammad Waleed Gondal, et al. ∙

∙ 02/19/2016

Depth-Based Object Tracking Using a Robust Gaussian Filter

We consider the problem of model-based 3D-tracking of objects given dens...

0 Jan Issac, et al. ∙

∙ 09/14/2015

Robust Gaussian Filtering using a Pseudo Measurement

Many sensors, such as range, sonar, radar, GPS and visual devices, produ...

0 Manuel Wüthrich, et al. ∙

∙ 04/29/2015

Probabilistic Depth Image Registration incorporating Nonvisual Information

In this paper, we derive a probabilistic registration algorithm for obje...

0 Manuel Wüthrich, et al. ∙

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