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20182023
most citedMultiwavelet-based Operator Learning for Differential Equations

67 citations · 67 across the 3 of their papers we have counts for

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8 papers · 1 filter

cs.LG2023

Neuro-Inspired Hierarchical Multimodal Learning

Xiongye Xiao, Gengshuo Liu, Gaurav Gupta +6

Integrating and processing information from various sources or modalities are critical for obtaining a comprehensive and accurate perception of the real world. Drawing inspiration…

cs.LG2023

Fractional dynamics foster deep learning of COPD stage prediction

Chenzhong Yin, Mihai Udrescu, Gaurav Gupta +6

Chronic obstructive pulmonary disease (COPD) is one of the leading causes of death worldwide. Current COPD diagnosis (i.e., spirometry) could be unreliable because the test depends…

cs.LG2023

Coupled Multiwavelet Neural Operator Learning for Coupled Partial Differential Equations

Xiongye Xiao, Defu Cao, Ruochen Yang +5

Coupled partial differential equations (PDEs) are key tasks in modeling the complex dynamics of many physical processes. Recently, neural operators have shown the ability to solve…

cs.LG202167 cited

Multiwavelet-based Operator Learning for Differential Equations

Gaurav Gupta, Xiongye Xiao, Paul Bogdan

The solution of a partial differential equation can be obtained by computing the inverse operator map between the input and the solution space. Towards this end, we introduce a \te…

cs.LG2021

Non-Markovian Reinforcement Learning using Fractional Dynamics

Gaurav Gupta, Chenzhong Yin, Jyotirmoy V. Deshmukh +1

Reinforcement learning (RL) is a technique to learn the control policy for an agent that interacts with a stochastic environment. In any given state, the agent takes some action, a…

cs.LG2019

Noisy Batch Active Learning with Deterministic Annealing

Gaurav Gupta, Anit Kumar Sahu, Wan-Yi Lin

We study the problem of training machine learning models incrementally with batches of samples annotated with noisy oracles. We select each batch of samples that are important and…