160 citations · 381 across the 19 of their papers we have counts for
20 papers
Within-person prediction of depressive symptom change using year-long Screenome data and CES-D assessments
Merve Cerit, Andrea Mock, Vryan Almanon Feliciano +4
Predicting whether an individual's depressive symptoms will worsen, remain stable, or improve over the coming weeks can enable earlier and more targeted care, yet prospective withi…
Curious Replay for Model-based Adaptation
Isaac Kauvar, Chris Doyle, Linqi Zhou +1
Agents must be able to adapt quickly as an environment changes. We find that existing model-based reinforcement learning agents are unable to do this well, in part because of how t…
Just One Byte (per gradient): A Note on Low-Bandwidth Decentralized Language Model Finetuning Using Shared Randomness
Eric Zelikman, Qian Huang, Percy Liang +2
Language model training in distributed settings is limited by the communication cost of gradient exchanges. In this short note, we extend recent work from Malladi et al. (2023), us…
Developmental Curiosity and Social Interaction in Virtual Agents
Chris Doyle, Sarah Shader, Michelle Lau +3
Infants explore their complex physical and social environment in an organized way. To gain insight into what intrinsic motivations may help structure this exploration, we create a…
Partial-View Object View Synthesis via Filtered Inversion
Fan-Yun Sun, Jonathan Tremblay, Valts Blukis +11
We propose Filtering Inversion (FINV), a learning framework and optimization process that predicts a renderable 3D object representation from one or few partial views. FINV address…
Parsel: Algorithmic Reasoning with Language Models by Composing Decompositions
Eric Zelikman, Qian Huang, Gabriel Poesia +2
Despite recent success in large language model (LLM) reasoning, LLMs struggle with hierarchical multi-step reasoning tasks like generating complex programs. For these tasks, humans…
Interaction Modeling with Multiplex Attention
Fan-Yun Sun, Isaac Kauvar, Ruohan Zhang +4
Modeling multi-agent systems requires understanding how agents interact. Such systems are often difficult to model because they can involve a variety of types of interactions that…
Challenges and Opportunities for Machine Learning Classification of Behavior and Mental State from Images
Peter Washington, Cezmi Onur Mutlu, Aaron Kline +7
Computer Vision (CV) classifiers which distinguish and detect nonverbal social human behavior and mental state can aid digital diagnostics and therapeutics for psychiatry and the b…
Training Affective Computer Vision Models by Crowdsourcing Soft-Target Labels
Peter Washington, Onur Cezmi Mutlu, Emilie Leblanc +8
Emotion classifiers traditionally predict discrete emotions. However, emotion expressions are often subjective, thus requiring a method to handle subjective labels. We explore the…
Improved Digital Therapy for Developmental Pediatrics Using Domain-Specific Artificial Intelligence: Machine Learning Study
Peter Washington, Haik Kalantarian, John Kent +16
Background: Automated emotion classification could aid those who struggle to recognize emotions, including children with developmental behavioral conditions such as autism. However…
Active World Model Learning with Progress Curiosity
Kuno Kim, Megumi Sano, Julian De Freitas +2
World models are self-supervised predictive models of how the world evolves. Humans learn world models by curiously exploring their environment, in the process acquiring compact ab…
ThreeDWorld: A Platform for Interactive Multi-Modal Physical Simulation
Chuang Gan, Jeremy Schwartz, Seth Alter +21
We introduce ThreeDWorld (TDW), a platform for interactive multi-modal physical simulation. TDW enables simulation of high-fidelity sensory data and physical interactions between m…
A Wearable Social Interaction Aid for Children with Autism
Nick Haber, Catalin Voss, Jena Daniels +7
With most recent estimates giving an incidence rate of 1 in 68 children in the United States, the autism spectrum disorder (ASD) is a growing public health crisis. Many of these ch…
Superpower Glass: Delivering Unobtrusive Real-time Social Cues in Wearable Systems
Catalin Voss, Peter Washington, Nick Haber +8
We have developed a system for automatic facial expression recognition, which runs on Google Glass and delivers real-time social cues to the wearer. We evaluate the system as a beh…
Designing a Holistic At-Home Learning Aid for Autism
Catalin Voss, Nick Haber, Peter Washington +8
In recent years, much focus has been put on employing technology to make novel behavioural aids for those with autism. Most of these are digital adaptations of tools used in standa…
Flexible Neural Representation for Physics Prediction
Damian Mrowca, Chengxu Zhuang, Elias Wang +4
Humans have a remarkable capacity to understand the physical dynamics of objects in their environment, flexibly capturing complex structures and interactions at multiple levels of…
Emergence of Structured Behaviors from Curiosity-Based Intrinsic Motivation
Nick Haber, Damian Mrowca, Li Fei-Fei +1
Infants are experts at playing, with an amazing ability to generate novel structured behaviors in unstructured environments that lack clear extrinsic reward signals. We seek to rep…
Learning to Play with Intrinsically-Motivated Self-Aware Agents
Nick Haber, Damian Mrowca, Li Fei-Fei +1
Infants are experts at playing, with an amazing ability to generate novel structured behaviors in unstructured environments that lack clear extrinsic reward signals. We seek to mat…
A normal form around a Lagrangian submanifold of radial points
Nick Haber
In this work we produce microlocal normal forms for pseudodifferential operators which have a Lagrangian submanifold of radial points. This answers natural questions about such ope…
Propagation of singularities around a Lagrangian submanifold of radial points
Nick Haber, András Vasy
In this work we study the wavefront set of a solution u to Pu = f, where P is a pseudodifferential operator on a manifold with real-valued homogeneous principal symbol p, when the…