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07/04/2022
Parametric and Multivariate Uncertainty Calibration for Regression and Object Detection
Reliable spatial uncertainty evaluation of object detection models is of...
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02/25/2022
Confidence Calibration for Object Detection and Segmentation
Calibrated confidence estimates obtained from neural networks are crucia...
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09/21/2021
Bayesian Confidence Calibration for Epistemic Uncertainty Modelling
Modern neural networks have found to be miscalibrated in terms of confid...
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08/04/2020
On Feature Relevance Uncertainty: A Monte Carlo Dropout Sampling Approach
Understanding decisions made by neural networks is key for the deploymen...
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12/13/2019
Dota 2 with Large Scale Deep Reinforcement Learning
On April 13th, 2019, OpenAI Five became the first AI system to defeat th...
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10/16/2019
Solving Rubik's Cube with a Robot Hand
We demonstrate that models trained only in simulation can be used to sol...
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02/26/2018
Multi-Goal Reinforcement Learning: Challenging Robotics Environments and Request for Research
The purpose of this technical report is two-fold. First of all, it intro...
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07/05/2017
Hindsight Experience Replay
Dealing with sparse rewards is one of the biggest challenges in Reinforc...
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03/21/2017
One-Shot Imitation Learning
Imitation learning has been commonly applied to solve different tasks in...
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10/11/2016
Transfer from Simulation to Real World through Learning Deep Inverse Dynamics Model
Developing control policies in simulation is often more practical and sa...
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06/05/2016