1 citations · 1 across the 8 of their papers we have counts for
8 papers
The Universe Learning Itself: On the Evolution of Dynamics from the Big Bang to Machine Intelligence
Pradeep Singh, Mudasani Rushikesh, Bezawada Sri Sai Anurag +1
We develop a unified, dynamical-systems narrative of the universe that traces a continuous chain of structure formation from the Big Bang to contemporary human societies and their…
Echo State Networks as State-Space Models: A Systems Perspective
Pradeep Singh, Balasubramanian Raman
Echo State Networks (ESNs) are typically presented as efficient, readout-trained recurrent models, yet their dynamics and design are often guided by heuristics rather than first pr…
HypER: Hyperbolic Echo State Networks for Capturing Stretch-and-Fold Dynamics in Chaotic Flows
Pradeep Singh, Sutirtha Ghosh, Ashutosh Kumar +2
Forecasting chaotic dynamics beyond a few Lyapunov times is difficult because infinitesimal errors grow exponentially. Existing Echo State Networks (ESNs) mitigate this growth but…
Frozen in Time: Parameter-Efficient Time Series Transformers via Reservoir-Induced Feature Expansion and Fixed Random Dynamics
Pradeep Singh, Mehak Sharma, Anupriya Dey +1
Transformers are the de-facto choice for sequence modelling, yet their quadratic self-attention and weak temporal bias can make long-range forecasting both expensive and brittle. W…
Contraction, Criticality, and Capacity: A Dynamical-Systems Perspective on Echo-State Networks
Pradeep Singh, Lavanya Sankaranarayanan, Balasubramanian Raman
Echo-State Networks (ESNs) distil a key neurobiological insight: richly recurrent but fixed circuitry combined with adaptive linear read-outs can transform temporal streams with re…
Dynamics and Computational Principles of Echo State Networks: A Mathematical Perspective
Pradeep Singh, Ashutosh Kumar, Sutirtha Ghosh +2
Reservoir computing (RC) represents a class of state-space models (SSMs) characterized by a fixed state transition mechanism (the reservoir) and a flexible readout layer that maps…
Biasing & Debiasing based Approach Towards Fair Knowledge Transfer for Equitable Skin Analysis
Anshul Pundhir, Balasubramanian Raman, Pravendra Singh
Deep learning models, particularly Convolutional Neural Networks (CNNs), have demonstrated exceptional performance in diagnosing skin diseases, often outperforming dermatologists.…
SOFIM: Stochastic Optimization Using Regularized Fisher Information Matrix
Mrinmay Sen, A. K. Qin, Gayathri C +3
This paper introduces a new stochastic optimization method based on the regularized Fisher information matrix (FIM), named SOFIM, which can efficiently utilize the FIM to approxima…