Search Results for author: Vwani Roychowdhury

Found 13 papers, 1 papers with code

Embed-Search-Align: DNA Sequence Alignment using Transformer Models

no code implementations20 Sep 2023 Pavan Holur, K. C. Enevoldsen, Shreyas Rajesh, Lajoyce Mboning, Thalia Georgiou, Louis-S. Bouchard, Matteo Pellegrini, Vwani Roychowdhury

In this framework, a novel encoder model DNA-ESA generates representations of reads and fragments of the reference, which are projected into a shared vector space where the read-fragment distance is used as surrogate for alignment.

Semantic Similarity Semantic Textual Similarity

Metalearning generalizable dynamics from trajectories

no code implementations3 Jan 2023 Qiaofeng Li, Tianyi Wang, Vwani Roychowdhury, M. Khalid Jawed

We present the interpretable meta neural ordinary differential equation (iMODE) method to rapidly learn generalizable (i. e., not parameter-specific) dynamics from trajectories of multiple dynamical systems that vary in their physical parameters.

Inductive Bias Meta-Learning

Action-conditioned On-demand Motion Generation

1 code implementation17 Jul 2022 QIUJING LU, YiPeng Zhang, Mingjian Lu, Vwani Roychowdhury

We propose a novel framework, On-Demand MOtion Generation (ODMO), for generating realistic and diverse long-term 3D human motion sequences conditioned only on action types with an additional capability of customization.

Contrastive Learning Human action generation

Quantum Advantage in Variational Bayes Inference

no code implementations7 Jul 2022 Hideyuki Miyahara, Vwani Roychowdhury

Variational Bayes (VB) inference algorithm is used widely to estimate both the parameters and the unobserved hidden variables in generative statistical models.

Unity

Quantum Approximation of Normalized Schatten Norms and Applications to Learning

no code implementations23 Jun 2022 Yiyou Chen, Hideyuki Miyahara, Louis-S. Bouchard, Vwani Roychowdhury

Efficient measures to determine similarity of quantum states, such as the fidelity metric, have been widely studied.

Diverse Imitation Learning via Self-Organizing Generative Models

no code implementations6 May 2022 Arash Vahabpour, Tianyi Wang, QIUJING LU, Omead Pooladzandi, Vwani Roychowdhury

Imitation learning is the task of replicating expert policy from demonstrations, without access to a reward function.

Imitation Learning

Which side are you on? Insider-Outsider classification in conspiracy-theoretic social media

no code implementations ACL 2022 Pavan Holur, Tianyi Wang, Shadi Shahsavari, Timothy Tangherlini, Vwani Roychowdhury

In these, an outside group threatens the integrity of an inside group, leading to the emergence of sharply defined group identities: Insiders -- agents with whom the authors identify and Outsiders -- agents who threaten the insiders.

Language Modelling

Ansatz-Independent Variational Quantum Classifier

no code implementations2 Feb 2021 Hideyuki Miyahara, Vwani Roychowdhury

Next, we propose a variational circuit realization (VCR) for designing efficient quantum circuits for a given unitary operator.

An automated pipeline for the discovery of conspiracy and conspiracy theory narrative frameworks: Bridgegate, Pizzagate and storytelling on the web

no code implementations23 Aug 2020 Timothy R. Tangherlini, Shadi Shahsavari, Behnam Shahbazi, Ehsan Ebrahimzadeh, Vwani Roychowdhury

We base this work on two separate repositories of posts and news articles describing the well-known conspiracy theory Pizzagate from 2016, and the New Jersey conspiracy Bridgegate from 2013.

Conspiracy in the Time of Corona: Automatic detection of Covid-19 Conspiracy Theories in Social Media and the News

no code implementations28 Apr 2020 Shadi Shahsavari, Pavan Holur, Timothy R. Tangherlini, Vwani Roychowdhury

Understanding the dynamics of storytelling on social media and the narrative frameworks that provide the generative basis for these stories may also be helpful for devising methods to disrupt their spread.

Brain-inspired automated visual object discovery and detection

no code implementations30 Sep 2019 Lichao Chen, Sudhir Singh, Thomas Kailath, Vwani Roychowdhury

This paper leverages the availability of such data to develop a scalable framework for unsupervised learning of object prototypes--brain-inspired flexible, scale, and shift invariant representations of deformable objects (e. g., humans, motorcycles, cars, airplanes) comprised of parts, their different configurations and views, and their spatial relationships.

Object Object Discovery

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