604 citations · 1.1k across the 31 of their papers we have counts for
9 papers · 1 filter
You Mostly Walk Alone: Analyzing Feature Attribution in Trajectory Prediction
Osama Makansi, Julius von Kügelgen, Francesco Locatello +4
Predicting the future trajectory of a moving agent can be easy when the past trajectory continues smoothly but is challenging when complex interactions with other agents are involv…
Multi-headed Neural Ensemble Search
Ashwin Raaghav Narayanan, Arber Zela, Tonmoy Saikia +2
Ensembles of CNN models trained with different seeds (also known as Deep Ensembles) are known to achieve superior performance over a single copy of the CNN. Neural Ensemble Search…
Pre-training of Deep RL Agents for Improved Learning under Domain Randomization
Artemij Amiranashvili, Max Argus, Lukas Hermann +2
Visual domain randomization in simulated environments is a widely used method to transfer policies trained in simulation to real robots. However, domain randomization and augmentat…
Scaling Imitation Learning in Minecraft
Artemij Amiranashvili, Nicolai Dorka, Wolfram Burgard +2
Imitation learning is a powerful family of techniques for learning sensorimotor coordination in immersive environments. We apply imitation learning to attain state-of-the-art perfo…
Understanding and Robustifying Differentiable Architecture Search
Arber Zela, Thomas Elsken, Tonmoy Saikia +3
Differentiable Architecture Search (DARTS) has attracted a lot of attention due to its simplicity and small search costs achieved by a continuous relaxation and an approximation of…
Robust Learning Under Label Noise With Iterative Noise-Filtering
Duc Tam Nguyen, Thi-Phuong-Nhung Ngo, Zhongyu Lou +3
We consider the problem of training a model under the presence of label noise. Current approaches identify samples with potentially incorrect labels and reduce their influence on t…