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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
About Me
About Me
Posts
Future Blog Post
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Blog Post number 4
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This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 3
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Blog Post number 2
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Blog Post number 1
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publications
Size Lowerbounds for Deep Operator Networks
Published in TMLR, 2024
Anirbit Mukherjee, Amartya Roy
WikiTransfer: Knowledge transfer from High-Resource to Low-Resource Language in Multilingual Wikipedia
Published in Wiki Workshop (11th edition) , 2024
Paramita Das, Amartya Roy, Animesh Mukherjee
talks
Size Lowerbounds for Deep Operator Networks (TMLR 2024)
Published:
Deep Operator Networks are an increasingly popular paradigm for solving regression in infinite dimensions and hence solve families of PDEs in one shot. In this work, we aim to establish a first-of-its-kind data-dependent lowerbound on the size of DeepONets required for them to be able to reduce empirical error on noisy data. In particular, we show that for low training errors to be obtained on n data points it is necessary that the common output dimension of the branch and the trunk net be scaling as Ω ( √4 n). This inspires our experiments with DeepONets solving the advection-diffusion-reaction PDE, where we demonstrate the possibility that at a fixed model size, to leverage increase in this common output dimension and get monotonic lowering of training error, the size of the training data might necessarily need to scale at least quadratically with it.