activity
20232026
most citedBeyond Euclid: An Illustrated Guide to Modern Machine Learning with Geometric, Topological, and Algebraic Structures

9 citations · 14 across the 7 of their papers we have counts for

collaborators

7 papers

cs.AI2026

Physics of Agents: Statistical Mechanics Predicts Collective Behavior of AI Agents

Batu El, Jinhee Paeng, Fatih Dinc +7

AI agents increasingly operate as part of interacting systems rather than in isolation. As agents exchange information and jointly make decisions, their interactions can improve co…

q-bio.NC2025

Latent computing by biological neural networks: A dynamical systems framework

Fatih Dinc, Marta Blanco-Pozo, David Klindt +8

Although individual neurons and neural populations exhibit the phenomenon of representational drift, perceptual and behavioral outputs of many neural circuits can remain stable acr…

q-bio.NC2025

Understanding and controlling the geometry of memory organization in RNNs

Udith Haputhanthri, Liam Storan, Yiqi Jiang +7

Training recurrent neural networks (RNNs) is a high-dimensional process that requires updating numerous parameters. Therefore, it is often difficult to pinpoint the underlying lear…

q-bio.NC2025

Dynamical phases of short-term memory mechanisms in RNNs

Bariscan Kurtkaya, Fatih Dinc, Mert Yuksekgonul +7

Short-term memory is essential for cognitive processing, yet our understanding of its neural mechanisms remains unclear. Neuroscience has long focused on how sequential activity pa…

cs.LG2025

A ghost mechanism: An analytical model of abrupt learning in recurrent networks

Fatih Dinc, Ege Cirakman, Bariscan Kurtkaya +4

Abrupt learning is a common phenomenon in recurrent neural networks (RNNs) trained on working memory tasks. In such cases, the networks develop transient slow regions in state spac…

cs.LG2024★ 9 cited

Beyond Euclid: An Illustrated Guide to Modern Machine Learning with Geometric, Topological, and Algebraic Structures

Mathilde Papillon, Sophia Sanborn, Johan Mathe +8

The enduring legacy of Euclidean geometry underpins classical machine learning, which, for decades, has been primarily developed for data lying in Euclidean space. Yet, modern mach…

q-bio.NC2023★ 5 cited

CORNN: Convex optimization of recurrent neural networks for rapid inference of neural dynamics

Fatih Dinc, Adam Shai, Mark Schnitzer +1

Advances in optical and electrophysiological recording technologies have made it possible to record the dynamics of thousands of neurons, opening up new possibilities for interpret…