135 citations · 157 across the 9 of their papers we have counts for
6 papers · 1 filter
Focus Group on Artificial Intelligence for Health
Marcel Salathé, Thomas Wiegand, Markus Wenzel
Artificial Intelligence (AI) - the phenomenon of machines being able to solve problems that require human intelligence - has in the past decade seen an enormous rise of interest du…
Adversarial Vision Challenge
Wieland Brendel, Jonas Rauber, Alexey Kurakin +5
The NIPS 2018 Adversarial Vision Challenge is a competition to facilitate measurable progress towards robust machine vision models and more generally applicable adversarial attacks…
Crowdbreaks: Tracking Health Trends using Public Social Media Data and Crowdsourcing
Martin Mueller, Marcel Salathé
In the past decade, tracking health trends using social media data has shown great promise, due to a powerful combination of massive adoption of social media around the world, and…
Learning to Run challenge solutions: Adapting reinforcement learning methods for neuromusculoskeletal environments
Łukasz Kidziński, Sharada Prasanna Mohanty, Carmichael Ong +26
In the NIPS 2017 Learning to Run challenge, participants were tasked with building a controller for a musculoskeletal model to make it run as fast as possible through an obstacle c…
Learning to Run challenge: Synthesizing physiologically accurate motion using deep reinforcement learning
Łukasz Kidziński, Sharada P. Mohanty, Carmichael Ong +5
Synthesizing physiologically-accurate human movement in a variety of conditions can help practitioners plan surgeries, design experiments, or prototype assistive devices in simulat…
Learning to Recognize Musical Genre from Audio
Michaël Defferrard, Sharada P. Mohanty, Sean F. Carroll +1
We here summarize our experience running a challenge with open data for musical genre recognition. Those notes motivate the task and the challenge design, show some statistics abou…