6.2k citations · 7.2k across the 26 of their papers we have counts for
29 papers
EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations
Yi-Lun Liao, Brandon Wood, Abhishek Das +1
Equivariant Transformers such as Equiformer have demonstrated the efficacy of applying Transformers to the domain of 3D atomistic systems. However, they are limited to small degree…
AdsorbML: A Leap in Efficiency for Adsorption Energy Calculations using Generalizable Machine Learning Potentials
Janice Lan, Aini Palizhati, Muhammed Shuaibi +6
Computational catalysis is playing an increasingly significant role in the design of catalysts across a wide range of applications. A common task for many computational methods is…
Open Challenges in Developing Generalizable Large Scale Machine Learning Models for Catalyst Discovery
Adeesh Kolluru, Muhammed Shuaibi, Aini Palizhati +6
The development of machine learned potentials for catalyst discovery has predominantly been focused on very specific chemistries and material compositions. While effective in inter…
Spherical Channels for Modeling Atomic Interactions
C. Lawrence Zitnick, Abhishek Das, Adeesh Kolluru +5
Modeling the energy and forces of atomic systems is a fundamental problem in computational chemistry with the potential to help address many of the world's most pressing problems,…
The Open Catalyst 2022 (OC22) Dataset and Challenges for Oxide Electrocatalysts
Richard Tran, Janice Lan, Muhammed Shuaibi +14
The development of machine learning models for electrocatalysts requires a broad set of training data to enable their use across a wide variety of materials. One class of materials…
Habitat-Web: Learning Embodied Object-Search Strategies from Human Demonstrations at Scale
Ram Ramrakhya, Eric Undersander, Dhruv Batra +1
We present a large-scale study of imitating human demonstrations on tasks that require a virtual robot to search for objects in new environments -- (1) ObjectGoal Navigation (e.g.…
GemNet-OC: Developing Graph Neural Networks for Large and Diverse Molecular Simulation Datasets
Johannes Gasteiger, Muhammed Shuaibi, Anuroop Sriram +4
Recent years have seen the advent of molecular simulation datasets that are orders of magnitude larger and more diverse. These new datasets differ substantially in four aspects of…
Towards Training Billion Parameter Graph Neural Networks for Atomic Simulations
Anuroop Sriram, Abhishek Das, Brandon M. Wood +2
Recent progress in Graph Neural Networks (GNNs) for modeling atomic simulations has the potential to revolutionize catalyst discovery, which is a key step in making progress toward…
NarrationBot and InfoBot: A Hybrid System for Automated Video Description
Shasta Ihorn, Yue-Ting Siu, Aditya Bodi +6
Video accessibility is crucial for blind and low vision users for equitable engagements in education, employment, and entertainment. Despite the availability of professional and am…
Auxiliary Tasks and Exploration Enable ObjectNav
Joel Ye, Dhruv Batra, Abhishek Das +1
ObjectGoal Navigation (ObjectNav) is an embodied task wherein agents are to navigate to an object instance in an unseen environment. Prior works have shown that end-to-end ObjectNa…
ForceNet: A Graph Neural Network for Large-Scale Quantum Calculations
Weihua Hu, Muhammed Shuaibi, Abhishek Das +5
With massive amounts of atomic simulation data available, there is a huge opportunity to develop fast and accurate machine learning models to approximate expensive physics-based ca…
An Introduction to Electrocatalyst Design using Machine Learning for Renewable Energy Storage
C. Lawrence Zitnick, Lowik Chanussot, Abhishek Das +14
Scalable and cost-effective solutions to renewable energy storage are essential to addressing the world's rising energy needs while reducing climate change. As we increase our reli…
Auxiliary Tasks Speed Up Learning PointGoal Navigation
Joel Ye, Dhruv Batra, Erik Wijmans +1
PointGoal Navigation is an embodied task that requires agents to navigate to a specified point in an unseen environment. Wijmans et al. showed that this task is solvable but their…
Feel The Music: Automatically Generating A Dance For An Input Song
Purva Tendulkar, Abhishek Das, Aniruddha Kembhavi +1
We present a general computational approach that enables a machine to generate a dance for any input music. We encode intuitive, flexible heuristics for what a 'good' dance is: the…
Probing Emergent Semantics in Predictive Agents via Question Answering
Abhishek Das, Federico Carnevale, Hamza Merzic +8
Recent work has shown how predictive modeling can endow agents with rich knowledge of their surroundings, improving their ability to act in complex environments. We propose questio…
Large-scale Pretraining for Visual Dialog: A Simple State-of-the-Art Baseline
Vishvak Murahari, Dhruv Batra, Devi Parikh +1
Prior work in visual dialog has focused on training deep neural models on VisDial in isolation. Instead, we present an approach to leverage pretraining on related vision-language d…
Improving Generative Visual Dialog by Answering Diverse Questions
Vishvak Murahari, Prithvijit Chattopadhyay, Dhruv Batra +2
Prior work on training generative Visual Dialog models with reinforcement learning(Das et al.) has explored a Qbot-Abot image-guessing game and shown that this 'self-talk' approach…
IR-VIC: Unsupervised Discovery of Sub-goals for Transfer in RL
Nirbhay Modhe, Prithvijit Chattopadhyay, Mohit Sharma +4
We propose a novel framework to identify sub-goals useful for exploration in sequential decision making tasks under partial observability. We utilize the variational intrinsic cont…
Embodied Question Answering in Photorealistic Environments with Point Cloud Perception
Erik Wijmans, Samyak Datta, Oleksandr Maksymets +6
To help bridge the gap between internet vision-style problems and the goal of vision for embodied perception we instantiate a large-scale navigation task -- Embodied Question Answe…
TarMAC: Targeted Multi-Agent Communication
Abhishek Das, Théophile Gervet, Joshua Romoff +4
We propose a targeted communication architecture for multi-agent reinforcement learning, where agents learn both what messages to send and whom to address them to while performing…
Neural Modular Control for Embodied Question Answering
Abhishek Das, Georgia Gkioxari, Stefan Lee +2
We present a modular approach for learning policies for navigation over long planning horizons from language input. Our hierarchical policy operates at multiple timescales, where t…
End-to-End Audio Visual Scene-Aware Dialog using Multimodal Attention-Based Video Features
Chiori Hori, Huda Alamri, Jue Wang +10
Dialog systems need to understand dynamic visual scenes in order to have conversations with users about the objects and events around them. Scene-aware dialog systems for real-worl…
Audio Visual Scene-Aware Dialog (AVSD) Challenge at DSTC7
Huda Alamri, Vincent Cartillier, Raphael Gontijo Lopes +8
Scene-aware dialog systems will be able to have conversations with users about the objects and events around them. Progress on such systems can be made by integrating state-of-the-…
Embodied Question Answering
Abhishek Das, Samyak Datta, Georgia Gkioxari +3
We present a new AI task -- Embodied Question Answering (EmbodiedQA) -- where an agent is spawned at a random location in a 3D environment and asked a question ("What color is the…