nips46

NeurIPS(NIPS) 2019 论文列表

NeurIPS 2019 Competition and Demonstration Track, 8-14 December 2019, Vancouver, Canada. Revised selected papers.

A Global Health Gym Environment for RL Applications.

Sekou L. Remy Oliver Bent

Towards Automated Deep Learning: Analysis of the AutoDL challenge series 2019.

Zhengying Liu Zhen Xu Shangeth Rajaa Meysam Madadi Júlio C. S. Jacques Júnior Sergio Escalera Adrien Pavao Sébastien Treguer Wei-Wei Tu Isabelle Guyon

The surprising efficiency of framing geo-spatial time series forecasting as a video prediction task - Insights from the IARAI Traffic4cast Competition at NeurIPS 2019.

David P. Kreil Michael K. Kopp David Jonietz Moritz Neun Aleksandra Gruca Pedro Herruzo Henry Martin Ali Soleymani Sepp Hochreiter

MicroNet for Efficient Language Modeling.

Zhongxia Yan Hanrui Wang Demi Guo Song Han

Retrospective Analysis of the 2019 MineRL Competition on Sample Efficient Reinforcement Learning.

Stephanie Milani Nicholay Topin Brandon Houghton William H. Guss Sharada P. Mohanty Keisuke Nakata Oriol Vinyals Noboru Sean Kuno

Visualizing and sonifying how an artificial ear hears music.

Vincent Herrmann

AirSim Drone Racing Lab.

Ratnesh Madaan Nicholas Gyde Sai Vemprala Matthew Brown Keiko Nagami Tim Taubner Eric Cristofalo Davide Scaramuzza Mac Schwager Ashish Kapoor

The Animal-AI Testbed and Competition.

Matthew Crosby Benjamin Beyret Murray Shanahan José Hernández-Orallo Lucy Cheke Marta Halina

Graph-ResNets for short-term traffic forecasts in almost unknown cities.

Henry Martin Dominik Bucher Ye Hong René Buffat Christian Rupprecht Martin Raubal

REAL-2019: Robot open-Ended Autonomous Learning competition.

Emilio Cartoni Francesco Mannella Vieri Giuliano Santucci Jochen Triesch Elmar Rueckert Gianluca Baldassarre

Empathic AI Painter: A Computational Creativity System with Embodied Conversational Interaction.

Özge Nilay Yalçin Nouf Abukhodair Steve DiPaola

The First International Competition in Machine Reconnaissance Blind Chess.

Ryan W. Gardner Corey Lowman Casey Richardson Ashley J. Llorens Jared Markowitz Nathan Drenkow Andrew Newman Gregory Clark Gino Perrotta Robert Perrotta Timothy Highley Vlad Shcherbina William Bernadoni Mark Jordan Asen Asenov

The Causality for Climate Competition.

Jakob Runge Xavier-Andoni Tibau Matthias Bruhns Jordi Muñoz-Marí Gustau Camps-Valls

Evolution Algorithm and Online Learning for Racing Drone.

Sangyun Shin Yongwon Kang Yong-Guk Kim

Catch Me, If You Can! A Mediated Perception Approach Towards Fully Autonomous Drone Racing.

Florian Ölsner Stefan Milz

F1TENTH: An Open-source Evaluation Environment for Continuous Control and Reinforcement Learning.

Matthew O'Kelly Hongrui Zheng Dhruv Karthik Rahul Mangharam

Sample Efficient Reinforcement Learning through Learning from Demonstrations in Minecraft.

Christian Scheller Yanick Schraner Manfred Vogel

Playing Minecraft with Behavioural Cloning.

Anssi Kanervisto Janne Karttunen Ville Hautamäki

Recurrent Autoencoder with Skip Connections and Exogenous Variables for Traffic Forecasting.

Pedro Herruzo Josep Lluís Larriba-Pey

A Deep-learning-aided Automatic Vision-based Control Approach for Autonomous Drone Racing in Game of Drones Competition.

Donghwi Kim Hyunjee Ryu Jedsadakorn Yonchorhor David Hyunchul Shim

Causal structure learning from time series: Large regression coefficients may predict causal links better in practice than small p-values.

Sebastian Weichwald Martin E. Jakobsen Phillip B. Mogensen Lasse Petersen Nikolaj Thams Gherardo Varando

Efficient Model for Image Classification With Regularization Tricks.

Taehyeon Kim Jonghyup Kim Seyoung Yun

NeurIPS 2019 Competition and Demonstration Track Revised selected papers.

Hugo Jair Escalante Raia Hadsell