no code implementations • 6 Jun 2018 • Saurabh Sahu, Rahul Gupta, Ganesh Sivaraman, Wael Abd-Almageed, Carol Espy-Wilson
Recently, generative adversarial networks and adversarial autoencoders have gained a lot of attention in machine learning community due to their exceptional performance in tasks such as digit classification and face recognition.
no code implementations • 16 May 2019 • Emre Yilmaz, Vikramjit Mitra, Ganesh Sivaraman, Horacio Franco
The rapid population aging has stimulated the development of assistive devices that provide personalized medical support to the needies suffering from various etiologies.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +1
2 code implementations • 22 Oct 2019 • Ganesh Sivaraman, Anand Narayanan Krishnamoorthy, Matthias Baur, Christian Holm, Marius Stan, Gabor Csányi, Chris Benmore, Álvaro Vázquez-Mayagoitia
We apply this scheme to a Hafnium dioxide (HfO2) dataset generated from a melt-quench ab initio molecular dynamics (AIMD) protocol.
1 code implementation • 9 Sep 2020 • Ganesh Sivaraman, Leighanne Gallington, Anand Narayanan Krishnamoorthy, Marius Stan, Gabor Csanyi, Alvaro Vazquez-Mayagoitia, Chris J. Benmore
Understanding the structure and properties of refractory oxides are critical for high temperature applications.
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.
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 • 6 Oct 2021 • Logan Ward, Ganesh Sivaraman, J. Gregory Pauloski, Yadu Babuji, Ryan Chard, Naveen Dandu, Paul C. Redfern, Rajeev S. Assary, Kyle Chard, Larry A. Curtiss, Rajeev Thakur, Ian Foster
Scientific applications that involve simulation ensembles can be accelerated greatly by using experiment design methods to select the best simulations to perform.
no code implementations • 11 Mar 2022 • Rahil Parikh, Nadee Seneviratne, Ganesh Sivaraman, Shihab Shamma, Carol Espy-Wilson
We used U. of Wisconsin X-ray Microbeam (XRMB) database of clean speech signals to train a feed-forward deep neural network (DNN) to estimate articulatory trajectories of six tract variables.
no code implementations • 25 May 2022 • Yashish M. Siriwardena, Ahmed Adel Attia, Ganesh Sivaraman, Carol Espy-Wilson
In this work, we compare and contrast different ways of doing data augmentation and show how this technique improves the performance of articulatory speech inversion not only on noisy speech, but also on clean speech data.
no code implementations • 27 May 2022 • Yashish M. Siriwardena, Ganesh Sivaraman, Carol Espy-Wilson
Multi-task learning (MTL) frameworks have proven to be effective in diverse speech related tasks like automatic speech recognition (ASR) and speech emotion recognition.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +3
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 • 1 Mar 2024 • Ganesh Sivaraman, Chris J. Benmore
Bridging the gap between diffuse x-ray or neutron scattering measurements and predicted structures derived from atom-atom pair potentials in disordered materials, has been a longstanding challenge in condensed matter physics.