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20242026
most citedA roadmap for AI in robotics

21 citations · 23 across the 9 of their papers we have counts for

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5 papers · 1 filter

cs.LG2025

Regularity and Stability Properties of Selective SSMs with Discontinuous Gating

Nikola Zubić, Davide Scaramuzza

Selective State-Space Models (SSMs) such as Mamba have become central to long-sequence modeling. Still, their stability is poorly understood: their state-space coefficients are mod…

cs.LG2025

Maximizing Asynchronicity in Event-based Neural Networks

Haiqing Hao, Nikola Zubić, Weihua He +3

Event cameras deliver visual data with high temporal resolution, low latency, and minimal redundancy, yet their asynchronous, sparse sequential nature challenges standard tensor-ba…

cs.LG2024

GG-SSMs: Graph-Generating State Space Models

Nikola Zubić, Davide Scaramuzza

State Space Models (SSMs) are powerful tools for modeling sequential data in computer vision and time series analysis domains. However, traditional SSMs are limited by fixed, one-d…

cs.LG20242 cited

S7: Selective and Simplified State Space Layers for Sequence Modeling

Taylan Soydan, Nikola Zubić, Nico Messikommer +2

A central challenge in sequence modeling is efficiently handling tasks with extended contexts. While recent state-space models (SSMs) have made significant progress in this area, t…

cs.LG2024

Limits of Deep Learning: Sequence Modeling through the Lens of Complexity Theory

Nikola Zubić, Federico Soldá, Aurelio Sulser +1

Despite their successes, deep learning models struggle with tasks requiring complex reasoning and function composition. We present a theoretical and empirical investigation into th…