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09/20/2023
Federated Learning with Neural Graphical Models
Federated Learning (FL) addresses the need to create models based on pro...
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08/10/2023
Knowledge Propagation over Conditional Independence Graphs
Conditional Independence (CI) graph is a special type of a Probabilistic...
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06/22/2023
DiversiGATE: A Comprehensive Framework for Reliable Large Language Models
In this paper, we introduce DiversiGATE, a unified framework that consol...
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03/21/2023
Are uGLAD? Time will tell!
We frequently encounter multiple series that are temporally correlated i...
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03/04/2023
MathPrompter: Mathematical Reasoning using Large Language Models
Large Language Models (LLMs) have limited performance when solving arith...
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02/27/2023
Neural Graph Revealers
Sparse graph recovery methods work well where the data follows their ass...
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11/13/2022
Methods for Recovering Conditional Independence Graphs: A Survey
Conditional Independence (CI) graphs are a type of probabilistic graphic...
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10/02/2022
Neural Graphical Models
Graphs are ubiquitous and are often used to understand the dynamics of a...
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05/23/2022
uGLAD: Sparse graph recovery by optimizing deep unrolled networks
Probabilistic Graphical Models (PGMs) are generative models of complex s...
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02/18/2021
Echo State Speech Recognition
We propose automatic speech recognition (ASR) models inspired by echo st...
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10/02/2019
AntMan: Sparse Low-Rank Compression to Accelerate RNN inference
Wide adoption of complex RNN based models is hindered by their inference...
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06/01/2019
Cooperative neural networks (CoNN): Exploiting prior independence structure for improved classification
We propose a new approach, called cooperative neural networks (CoNN), wh...
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06/01/2019