activity
20172026
most citedVariational Sampling of Temporal Trajectories

1 citations · 2 across the 5 of their papers we have counts for

collaborators

7 papers

cs.LG2026

MnemoDyn: Learning Resting State Dynamics from 40K FMRI sequences

Sourav Pal, Viet Luong, Hoseok Lee +5

We present a dynamical-systems based model for resting-state functional magnetic resonance imaging (rs-fMRI), trained on a dataset of roughly 40K rs-fMRI sequences covering a wide…

q-bio.GN2025

Brain-wide interpolation and conditioning of gene expression in the human brain using Implicit Neural Representations

Xizheng Yu, Justin Torok, Sneha Pandya +3

In this paper, we study the efficacy and utility of recent advances in non-local, non-linear image interpolation and extrapolation algorithms, specifically, ideas based on Implicit…

cs.LG2024★ 1 cited

Variational Sampling of Temporal Trajectories

Jurijs Nazarovs, Zhichun Huang, Xingjian Zhen +3

A deterministic temporal process can be determined by its trajectory, an element in the product space of (a) initial condition and (b) transition function $f:…

cs.LG2022★ 1 cited

Multi Resolution Analysis (MRA) for Approximate Self-Attention

Zhanpeng Zeng, Sourav Pal, Jeffery Kline +2

Transformers have emerged as a preferred model for many tasks in natural langugage processing and vision. Recent efforts on training and deploying Transformers more efficiently hav…

cs.CV2022

Deep Unlearning via Randomized Conditionally Independent Hessians

Ronak Mehta, Sourav Pal, Vikas Singh +1

Recent legislation has led to interest in machine unlearning, i.e., removing specific training samples from a predictive model as if they never existed in the training dataset. Unl…

cs.CV2018

Visual Attention for Behavioral Cloning in Autonomous Driving

Sourav Pal, Tharun Mohandoss, Pabitra Mitra

The goal of our work is to use visual attention to enhance autonomous driving performance. We present two methods of predicting visual attention maps. The first method is a supervi…

cs.CV2017

Saliency Prediction for Mobile User Interfaces

Prakhar Gupta, Shubh Gupta, Ajaykrishnan Jayagopal +2

We introduce models for saliency prediction for mobile user interfaces. A mobile interface may include elements like buttons, text, etc. in addition to natural images which enable…