682 citations · 874 across the 11 of their papers we have counts for
11 papers
Szegő-type determinant asymptotics for generalized Hilbert matrices with edge eigenvalues
Martin Gebert, Heinrich Küttler
We compute the large- asymptotics of the determinant of the identity plus or minus a generalized Hilbert matrix. For and $δ\in \mathbb{R} \setminus \{-1, -2,…
Dungeons and Data: A Large-Scale NetHack Dataset
Eric Hambro, Roberta Raileanu, Danielle Rothermel +4
Recent breakthroughs in the development of agents to solve challenging sequential decision making problems such as Go, StarCraft, or DOTA, have relied on both simulated environment…
MiniHack the Planet: A Sandbox for Open-Ended Reinforcement Learning Research
Mikayel Samvelyan, Robert Kirk, Vitaly Kurin +7
Progress in deep reinforcement learning (RL) is heavily driven by the availability of challenging benchmarks used for training agents. However, benchmarks that are widely adopted b…
Learning with AMIGo: Adversarially Motivated Intrinsic Goals
Andres Campero, Roberta Raileanu, Heinrich Küttler +3
A key challenge for reinforcement learning (RL) consists of learning in environments with sparse extrinsic rewards. In contrast to current RL methods, humans are able to learn new…
TorchBeast: A PyTorch Platform for Distributed RL
Heinrich Küttler, Nantas Nardelli, Thibaut Lavril +4
TorchBeast is a platform for reinforcement learning (RL) research in PyTorch. It implements a version of the popular IMPALA algorithm for fast, asynchronous, parallel training of R…
Kickstarting Deep Reinforcement Learning
Simon Schmitt, Jonathan J. Hudson, Augustin Zidek +8
We present a method for using previously-trained 'teacher' agents to kickstart the training of a new 'student' agent. To this end, we leverage ideas from policy distillation and po…
StarCraft II: A New Challenge for Reinforcement Learning
Oriol Vinyals, Timo Ewalds, Sergey Bartunov +22
This paper introduces SC2LE (StarCraft II Learning Environment), a reinforcement learning environment based on the StarCraft II game. This domain poses a new grand challenge for re…
DeepMind Lab
Charles Beattie, Joel Z. Leibo, Denis Teplyashin +18
DeepMind Lab is a first-person 3D game platform designed for research and development of general artificial intelligence and machine learning systems. DeepMind Lab can be used to s…
The exponent in the orthogonality catastrophe for Fermi gases
Martin Gebert, Heinrich Küttler, Peter Müller +1
We quantify the asymptotic vanishing of the ground-state overlap of two non-interacting Fermi gases in -dimensional Euclidean space in the thermodynamic limit. Given two one-par…
Anderson's orthogonality catastrophe
Martin Gebert, Heinrich Küttler, Peter Müller
We give an upper bound on the modulus of the ground-state overlap of two non-interacting fermionic quantum systems with particles in a large but finite volume of -dime…
Anderson's Orthogonality Catastrophe for One-dimensional Systems
Heinrich Küttler, Peter Otte, Wolfgang Spitzer
We derive rigorously the leading asymptotics of the so-called Anderson integral in the thermodynamic limit for one-dimensional, non-relativistic, spin-less Fermi systems. The coeff…