1 code implementation • 15 Feb 2024 • Henry W. Sprueill, Carl Edwards, Khushbu Agarwal, Mariefel V. Olarte, Udishnu Sanyal, Conrad Johnston, Hongbin Liu, Heng Ji, Sutanay Choudhury
The discovery of new catalysts is essential for the design of new and more efficient chemical processes in order to transition to a sustainable future.
no code implementations • 9 Feb 2024 • Stefan Dernbach, Khushbu Agarwal, Alejandro Zuniga, Michael Henry, Sutanay Choudhury
For example, can we query a LLM to identify the optimal contact in a professional network for a specific goal, based on relationships and attributes in a private database?
no code implementations • 8 Nov 2023 • Hongwu Peng, Caiwen Ding, Tong Geng, Sutanay Choudhury, Kevin Barker, Ang Li
The relentless advancement of artificial intelligence (AI) and machine learning (ML) applications necessitates the development of specialized hardware accelerators capable of handling the increasing complexity and computational demands.
1 code implementation • 22 Oct 2023 • Henry W. Sprueill, Carl Edwards, Mariefel V. Olarte, Udishnu Sanyal, Heng Ji, Sutanay Choudhury
Discovering novel catalysts requires complex reasoning involving multiple chemical properties and resultant trade-offs, leading to a combinatorial growth in the search space.
1 code implementation • 23 May 2023 • Andrew Engel, Zhichao Wang, Natalie S. Frank, Ioana Dumitriu, Sutanay Choudhury, Anand Sarwate, Tony Chiang
A second trend has been to utilize kernel functions in various explain-by-example or data attribution tasks.
no code implementations • 4 May 2023 • Jou-An Chen, Hsin-Hsuan Sung, Xipeng Shen, Sutanay Choudhury, Ang Li
It fills the gap by proposing a series of abstractions and techniques to map binary GNNs and their computations best to fit the nature of bit manipulations on GPUs.
2 code implementations • 15 Mar 2023 • Logan Ward, J. Gregory Pauloski, Valerie Hayot-Sasson, Ryan Chard, Yadu Babuji, Ganesh Sivaraman, Sutanay Choudhury, Kyle Chard, Rajeev Thakur, Ian Foster
Applications that fuse machine learning and simulation can benefit from the use of multiple computing resources, with, for example, simulation codes running on highly parallel supercomputers and AI training and inference tasks on specialized accelerators.
no code implementations • 25 Nov 2022 • Hatem Helal, Jesun Firoz, Jenna Bilbrey, Mario Michael Krell, Tom Murray, Ang Li, Sotiris Xantheas, Sutanay Choudhury
Molecular property calculations are the bedrock of chemical physics.
1 code implementation • 8 Nov 2022 • Jenna A. Bilbrey, Kristina M. Herman, Henry Sprueill, Soritis S. Xantheas, Payel Das, Manuel Lopez Roldan, Mike Kraus, Hatem Helal, Sutanay Choudhury
The demonstrated success of transfer learning has popularized approaches that involve pretraining models from massive data sources and subsequent finetuning towards a specific task.
1 code implementation • 9 Jun 2022 • Mehrdad Khatir, Nurendra Choudhary, Sutanay Choudhury, Khushbu Agarwal, Chandan K. Reddy
Such an approach enables us to propose a hyperbolic normalization layer and to further simplify the entire hyperbolic model to a Euclidean model cascaded with our hyperbolic normalization layer.
no code implementations • 24 May 2022 • Andrew Engel, Zhichao Wang, Anand D. Sarwate, Sutanay Choudhury, Tony Chiang
We introduce torchNTK, a python library to calculate the empirical neural tangent kernel (NTK) of neural network models in the PyTorch framework.
no code implementations • 16 Feb 2022 • Sai Pushpak Nandanoori, Sheng Guan, Soumya Kundu, Seemita Pal, Khushbu Agarwal, Yinghui Wu, Sutanay Choudhury
In particular, accurate and timely prediction of the (electro-mechanical) transient dynamic trajectories of the power grid is necessary for early detection of any instability and prevention of catastrophic failures.
no code implementations • 1 Aug 2021 • Ping Wang, Tian Shi, Khushbu Agarwal, Sutanay Choudhury, Chandan K. Reddy
On the other hand, the aspects, entity and context, limit the answers by node-specific information and lead to higher precision and lower recall.
Knowledge Base Question Answering Machine Reading Comprehension
1 code implementation • 7 May 2021 • Jenna Bilbrey, Logan Ward, Sutanay Choudhury, Neeraj Kumar, Ganesh Sivaraman
We examine a pair of graph generative models for the therapeutic design of novel drug candidates targeting SARS-CoV-2 viral proteins.
1 code implementation • 9 Feb 2021 • Logan Ward, Jenna A. Bilbrey, Sutanay Choudhury, Neeraj Kumar, Ganesh Sivaraman
Design of new drug compounds with target properties is a key area of research in generative modeling.
no code implementations • 30 Nov 2020 • Sutanay Choudhury, Jenna A. Bilbrey, Logan Ward, Sotiris S. Xantheas, Ian Foster, Joseph P. Heindel, Ben Blaiszik, Marcus E. Schwarting
Intermolecular and long-range interactions are central to phenomena as diverse as gene regulation, topological states of quantum materials, electrolyte transport in batteries, and the universal solvation properties of water.
1 code implementation • 22 Jul 2020 • Ping Wang, Khushbu Agarwal, Colby Ham, Sutanay Choudhury, Chandan K. Reddy
Representation learning methods for heterogeneous networks produce a low-dimensional vector embedding for each node that is typically fixed for all tasks involving the node.
1 code implementation • 19 Jul 2019 • Khushbu Agarwal, Tome Eftimov, Raghavendra Addanki, Sutanay Choudhury, Suzanne Tamang, Robert Rallo
Representation learning methods that transform encoded data (e. g., diagnosis and drug codes) into continuous vector spaces (i. e., vector embeddings) are critical for the application of deep learning in healthcare.
2 code implementations • 24 Jan 2018 • Patrick Mackey, Katherine Porterfield, Erin Fitzhenry, Sutanay Choudhury, George Chin Jr
Many real world networks are considered temporal networks, in which the chronological ordering of the edges has importance to the meaning of the data.
Data Structures and Algorithms
1 code implementation • 7 Sep 2017 • Arun V. Sathanur, Sutanay Choudhury, Cliff Joslyn, Sumit Purohit
In this work we tackle the problem of capturing the statistical dependence of the edge connectivity on the vertex labels and using the same distribution to regenerate property graphs of the same or expanded size in a scalable manner.
Social and Information Networks
no code implementations • 14 Jan 2016 • Baichuan Zhang, Sutanay Choudhury, Mohammad Al Hasan, Xia Ning, Khushbu Agarwal, Sumit Purohit, Paola Pesntez Cabrera
Link prediction, or predicting the likelihood of a link in a knowledge graph based on its existing state is a key research task.
no code implementations • 23 Dec 2015 • Pin-Yu Chen, Sutanay Choudhury, Alfred O. Hero
Many modern datasets can be represented as graphs and hence spectral decompositions such as graph principal component analysis (PCA) can be useful.
no code implementations • 14 Jul 2014 • Sutanay Choudhury, Chase Dowling
Given data sources such as social media streams and web pages Entity Linking is the task of mapping named entities that are extracted from the data to those present in the Knowledge Graph.