activity
20122026
most citedBiologically inspired sleep algorithm for artificial neural networks

10 citations · 17 across the 6 of their papers we have counts for

collaborators

7 papers

cs.LG2026

Stream Recursion Model (SRM)

Asael Sorensen, Charles Brock, David Chamberlain +3

Mechanistic interpretability seeks to make verifiable statements about the internal behavior of large language models (LLMs). Many interpretability techniques struggle to scale wit…

astro-ph.IM2024★ 2 cited

Reinforcement Learning for Data-Driven Workflows in Radio Interferometry. I. Principal Demonstration in Calibration

Brian M. Kirk, Urvashi Rau, Ramyaa Ramyaa

Radio interferometry is an observational technique used to study astrophysical phenomena. Data gathered by an interferometer requires substantial processing before astronomers can…

cs.LG2021★ 1 cited

Learning with distributional inverters

Eric Binnendyk, Marco Carmosino, Antonina Kolokolova +2

We generalize the "indirect learning" technique of Furst et. al., 1991 to reduce from learning a concept class over a samplable distribution to learning the same concept class…

cs.NE2019★ 10 cited

Biologically inspired sleep algorithm for artificial neural networks

Giri P Krishnan, Timothy Tadros, Ramyaa Ramyaa +1

Sleep plays an important role in incremental learning and consolidation of memories in biological systems. Motivated by the processes that are known to be involved in sleep generat…

cs.PL2015

Denotational cost semantics for functional languages with inductive types

Norman Danner, Daniel R. Licata, Ramyaa Ramyaa

A central method for analyzing the asymptotic complexity of a functional program is to extract and then solve a recurrence that expresses evaluation cost in terms of input size. Th…

cs.CC2013

Power of Nondetreministic JAGs on Cayley graphs

Martin Hofmann, Ramyaa Ramyaa

The Immerman-Szelepcsenyi Theorem uses an algorithm for co-st- connectivity based on inductive counting to prove that NLOGSPACE is closed un- der complementation. We want to invest…

cs.CC2012★ 4 cited

Implicit complexity for coinductive data: a characterization of corecurrence

Daniel Leivant, Ramyaa Ramyaa

We propose a framework for reasoning about programs that manipulate coinductive data as well as inductive data. Our approach is based on using equational programs, which support a…