activity
20192026
most citedMultitask Learning of Temporal Connectionism in Convolutional Networks using a Joint Distribution Loss Function to Simultaneously Identify Tools and Phase in Surgical Videos

13 citations · 35 across the 10 of their papers we have counts for

collaborators

10 papers

cs.LG2026

LORA-CRAFT: Cross-layer Rank Adaptation via Frozen Tucker Decomposition of Pre-trained Attention Weights

Kasun Dewage, Marianna Pensky, Suranadi De Silva +1

We introduce LoRA-CRAFT (\textbf{C}ross-layer \textbf{R}ank \textbf{A}daptation via \textbf{F}rozen \textbf{T}ucker), abbreviated CRAFT throughout, an extremely parameter-efficient…

cs.CV2024

Slot Abstractors: Toward Scalable Abstract Visual Reasoning

Shanka Subhra Mondal, Jonathan D. Cohen, Taylor W. Webb

Abstract visual reasoning is a characteristically human ability, allowing the identification of relational patterns that are abstracted away from object features, and the systemati…

cs.AI2023★ 3 cited

Improving Planning with Large Language Models: A Modular Agentic Architecture

Taylor Webb, Shanka Subhra Mondal, Ida Momennejad

Large language models (LLMs) demonstrate impressive performance on a wide variety of tasks, but they often struggle with tasks that require multi-step reasoning or goal-directed pl…

cs.CV2023★ 6 cited

Systematic Visual Reasoning through Object-Centric Relational Abstraction

Taylor W. Webb, Shanka Subhra Mondal, Jonathan D. Cohen

Human visual reasoning is characterized by an ability to identify abstract patterns from only a small number of examples, and to systematically generalize those patterns to novel i…

cs.LG2023

Determinantal Point Process Attention Over Grid Cell Code Supports Out of Distribution Generalization

Shanka Subhra Mondal, Steven Frankland, Taylor Webb +1

Deep neural networks have made tremendous gains in emulating human-like intelligence, and have been used increasingly as ways of understanding how the brain may solve the complex c…

cs.CV2023★ 7 cited

Learning to reason over visual objects

Shanka Subhra Mondal, Taylor Webb, Jonathan D. Cohen

A core component of human intelligence is the ability to identify abstract patterns inherent in complex, high-dimensional perceptual data, as exemplified by visual reasoning tasks…

cs.DC2019★ 5 cited

DeepPlace: Learning to Place Applications in Multi-Tenant Clusters

Subrata Mitra, Shanka Subhra Mondal, Nikhil Sheoran +3

Large multi-tenant production clusters often have to handle a variety of jobs and applications with a variety of complex resource usage characteristics. It is non-trivial and non-o…

q-fin.ST2019★ 1 cited

Investment Ranking Challenge: Identifying the best performing stocks based on their semi-annual returns

Shanka Subhra Mondal, Sharada Prasanna Mohanty, Benjamin Harlander +7

In the IEEE Investment ranking challenge 2018, participants were asked to build a model which would identify the best performing stocks based on their returns over a forward six mo…

cs.CV2019

KarNet: An Efficient Boolean Function Simplifier

Shanka Subhra Mondal, Abhilash Nandy, Ritesh Agrawal +1

Many approaches such as Quine-McCluskey algorithm, Karnaugh map solving, Petrick's method and McBoole's method have been devised to simplify Boolean expressions in order to optimiz…

eess.IV2019★ 13 cited

Multitask Learning of Temporal Connectionism in Convolutional Networks using a Joint Distribution Loss Function to Simultaneously Identify Tools and Phase in Surgical Videos

Shanka Subhra Mondal, Rachana Sathish, Debdoot Sheet

Surgical workflow analysis is of importance for understanding onset and persistence of surgical phases and individual tool usage across surgery and in each phase. It is beneficial…