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AIMS CDT students papers accepted at NeurIPS 2019

AIMS logo, part of Oxford's Engineering Department Research Group

A list of all papers by AIMS CDT students, accepted at NeurIPS this year can be found below:

The paper acceptances were announced on September 3, and the full list of accepted papers is here:

  • VIREL: A Variational Inference Framework for Reinforcement Learning. Matthew Fellows (University of Oxford) · Anuj Mahajan (University of Oxford) · Tim G. J. Rudner (University of Oxford) · Shimon Whiteson (University of Oxford).  (received a spotlight talk at NeurIPS (awarded to the top 3% of submitted papers/top 10% of accepted papers).
  • BatchBALD: Efficient and Diverse Batch Acquisition for Deep Bayesian Active Learning Andreas Kirsch (University of Oxford) · Joost van Amersfoort (University of Oxford) · Yarin Gal (University of Oxford).
  • Loaded DiCE: Trading off Bias and Variance in Any-Order Score Function Gradient Estimators for Reinforcement Learning. Gregory Farquhar (University of Oxford) · Shimon Whiteson (University of Oxford) · Jakob Foerster (University of Oxford).
  • Multi-Agent Common Knowledge Reinforcement Learning.  Christian Schroeder de Witt (University of Oxford) · Jakob Foerster (University of Oxford) · Gregory Farquhar (University of Oxford) · Philip Torr (University of Oxford) · Wendelin Boehmer (University of Oxford) · Shimon Whiteson (University of Oxford).
  • Generalization in Reinforcement Learning with Selective Noise Injection and Information BottleneckMaximilian Igl (University of Oxford) · Kamil Ciosek (Microsoft) · Yingzhen Li (Microsoft Research Cambridge) · Sebastian Tschiatschek (Microsoft Research) · Cheng Zhang (Microsoft) · Sam Devlin (Microsoft Research) · Katja Hofmann (Microsoft Research).
  • Fast Efficient Hyperparameter Tuning for Policy Gradient Methods.  Supratik Paul (University of Oxford) · Vitaly Kurin (RWTH Aachen University) · Shimon Whiteson (University of Oxford).
  • Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model.  Atilim Gunes Baydin (University of Oxford) · Lei Shao (Intel Corporation) · Wahid Bhimji (Berkeley lab) · Lukas Heinrich (New York University) · Saeid Naderiparizi (University of British Columbia) · Andreas Munk (University of British Columbia) · Jialin Liu (Lawrence Berkeley National Lab) · Bradley J Gram-Hansen (University of Oxford) · Gilles Louppe (University of Liège) · Lawrence Meadows (Intel Corporation) · Philip Torr (University of Oxford) · Victor Lee (Intel Corporation) · Kyle Cranmer (New York University) · Mr. Prabhat (LBL/NERSC) · Frank Wood (University of British Columbia).