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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
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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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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 2
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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 1
Published:
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.
publications
Automated Detection of Solar Radio Bursts Using a Statistical Method
Dayal Singh, Sasikumar Raja, Prasad Subramanian, R. Ramesh, and Christian Monstein, Solar Physics 294, 112 (2019)We developed an automated method to detect solar radio bursts from the dynamical spectrographs, and analyzed the origin of the detected solar radio bursts.
Finding SeMo: large scale linear motif detection and protein function annotation
Dayal Singh, Ankit Roy, Sanjana Nair, MS Madhusudhan, Under reviewWe develop a de-novo method for predicting Short Linear Motifs (SLiMs) in protein sequences. We use Finding SeMo to find motifs across all species and use them to predict functions of uncharacterized protein sequences.
Inferring long memory using extreme events
Dayal Singh Kalra and M. S. Santhanam, Chaos 31, 113131 (2021)We study extreme events in time series with long-range correlations. We find that it is possible to infer the long memory of time series just by extreme events.
Initializing ReLU networks in an expressive subspace of weights
Dayal Singh and G J Sreejith, Under reviewWe analyze signal propagation in ReLU networks with anti-correlated weights and demonstrate that it has an order-to-chaos phase transition, unlike the uncorrelated case. Furthermore, we demonstrate that ReLU networks initialized at this criticality train faster.
research
Statistical physics of Deep Neural Networks
In the past few years, there has been some progress in understanding Deep Neural Networks (DNNs) through ideas from statistical physics. These studies have shed light on various theoretical questions about DNNs. This includes, their function space and generalization properties. For my master’s thesis, I have worked on the information propagation in Deep ReLU networks with correlated weights. In particular, we show that ReLU networks with anti-correlated weights have an order-to-chaos criticality, unlike the uncorrelated weight case. Furthermore, we propose intializing ReLU networks at this criticality, and demonstrate that ReLU networks with anti-correlated intialization train faster. ArXiv link to the paper.
talks
The mean-field theory of deep neural networks?
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