11 papers
Looped SSMs: Depth-Recurrence and Input Reshaping for Time Series Classification
Mónika Farsang, Ramin Hasani, Daniela Rus +1
State Space Models (SSMs) are inherently recurrent along the sequence dimension, yet depth-recurrence - reusing the same block repeatedly across layers, as recently applied in loop…
Towards Safe Learning-Based Non-Linear Model Predictive Control through Recurrent Neural Network Modeling
Mihaela-Larisa Clement, Mónika Farsang, Agnes Poks +4
The practical deployment of nonlinear model predictive control (NMPC) is often limited by online computation: solving a nonlinear program at high control rates can be expensive on…
Single molecule localization microscopy challenge: a biologically inspired benchmark for long-sequence modeling
Fatemeh Valeh, Monika Farsang, Radu Grosu +1
State space models (SSMs) have recently achieved strong performance on long sequence modeling tasks while offering improved memory and computational efficiency compared to transfor…
Synaptic Activation and Dual Liquid Dynamics for Interpretable Bio-Inspired Models
Mónika Farsang, Radu Grosu
In this paper, we present a unified framework for various bio-inspired models to better understand their structural and functional differences. We show that liquid-capacitance-exte…
Adaptive Control in Autonomous Driving via Real-Time Recurrent RL
Julian Lemmel, Felix Resch, Mónika Farsang +3
We study online fine-tuning of pretrained control policies for autonomous driving using Real-Time Recurrent Reinforcement Learning (RTRRL), a memory-efficient algorithm that update…
Differential Gated Self-Attention
Elpiniki Maria Lygizou, Mónika Farsang, Radu Grosu
Transformers excel across a large variety of tasks but remain susceptible to corrupted inputs, since standard self-attention treats all query-key interactions uniformly. Inspired b…