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Found 14 papers, 8 papers with code
Could ChatGPT get an Engineering Degree? Evaluating Higher Education Vulnerability to AI Assistants
We investigate the potential scale of this vulnerability by measuring the degree to which AI assistants can complete assessment questions in standard university-level STEM courses.
The Food Recognition Benchmark: Using DeepLearning to Recognize Food on Images
The automatic recognition of food on images has numerous interesting applications, including nutritional tracking in medical cohorts.
Addressing machine learning concept drift reveals declining vaccine sentiment during the COVID-19 pandemic
We show that while vaccine sentiment has declined considerably during the COVID-19 pandemic in 2020, algorithms trained on pre-pandemic data would have largely missed this decline due to concept drift.
Experts and authorities receive disproportionate attention on Twitter during the COVID-19 crisis
Timely access to accurate information is crucial during the COVID-19 pandemic.
Social and Information Networks
Decentralized Privacy-Preserving Proximity Tracing
This document describes and analyzes a system for secure and privacy-preserving proximity tracing at large scale.
Cryptography and Security Computers and Society
COVID-Twitter-BERT: A Natural Language Processing Model to Analyse COVID-19 Content on Twitter
In this work, we release COVID-Twitter-BERT (CT-BERT), a transformer-based model, pretrained on a large corpus of Twitter messages on the topic of COVID-19.
Artificial Intelligence for Prosthetics - challenge solutions
In the NeurIPS 2018 Artificial Intelligence for Prosthetics challenge, participants were tasked with building a controller for a musculoskeletal model with a goal of matching a given time-varying velocity vector.
Focus Group on Artificial Intelligence for Health
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 due to significant advances in effectiveness and use.
Adversarial Vision Challenge
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
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 increasingly potent hardware and software that enables us to work with these new big data streams.
Learning to Run challenge solutions: Adapting reinforcement learning methods for neuromusculoskeletal environments
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 course.
Learning to Run challenge: Synthesizing physiologically accurate motion using deep reinforcement learning
Synthesizing physiologically-accurate human movement in a variety of conditions can help practitioners plan surgeries, design experiments, or prototype assistive devices in simulated environments, reducing time and costs and improving treatment outcomes.
Learning to Recognize Musical Genre from Audio
We here summarize our experience running a challenge with open data for musical genre recognition.
On the Ground Validation of Online Diagnosis with Twitter and Medical Records
Taking a different approach, we develop a novel system for social-media based disease detection at the individual level using a sample of professionally diagnosed individuals.
