731 citations · 3.7k across the 53 of their papers we have counts for
54 papers
Tensor formalism for predicting synaptic connections with ensemble modeling or optimization
Tirthabir Biswas, Tianzhi Lambus Li, Selimzhan Chalyshkan +2
Theoretical neuroscientists often try to understand how the structure of a neural network relates to its function by focusing on structural features that would either follow from o…
Geometric framework to predict structure from function in neural networks
Tirthabir Biswas, James E. Fitzgerald
Neural computation in biological and artificial networks relies on the nonlinear summation of many inputs. The structural connectivity matrix of synaptic weights between neurons is…
Consistent Higher Derivative Gravitational theories with stable de Sitter and Anti-de Sitter Backgrounds
Tirthabir Biswas, Alexey S. Koshelev, Anupam Mazumdar
In this paper we provide the criteria for any generally covariant, parity preserving, and torsion free theory of gravity to possess a stable de Sitter (dS) or anti-de Sitter (AdS)…
Gravitational theories with stable (anti-)de Sitter backgrounds
Tirthabir Biswas, Alexey S. Koshelev, Anupam Mazumdar
In this article we will construct the most general torsion-free parity-invariant covariant theory of gravity that is free from ghost-like and tachyonic nstabilities around constant…
Perturbations in Bouncing and Cyclic Models, a General Study
Tirthabir Biswas, Riley Mayes, Colleen Lattyak
Being able to reliably track perturbations across bounces and turnarounds in cyclic and bouncing cosmology lies at the heart of being able to compare the predictions of these model…
String-Inspired Infinite-Derivative Theories of Gravity: A Brief Overview
Tirthabir Biswas, Spyridon Talaganis
In String Theory there often appears a rather interesting class of higher derivative theories containing an infinite set of derivatives in the form of an exponential. These theorie…