4 papers · 1 filter
Neither Adversarial Training Nor Purification: Emergent Adversarial Robustness from Oscillatory Predictive Learning
Mohammed-Yassine Habibi, Klea Ziu, Martin Takáč +1
Adversarial robustness in computer vision is still largely achieved through adversarial training or test-time adversarial purification, both of which introduce significant computat…
WaveSSM: Multiscale State-Space Models for Non-stationary Signal Attention
Ruben Solozabal, Velibor Bojkovic, Hilal Alquabeh +3
State-space models (SSMs) have emerged as a powerful foundation for long-range sequence modeling, with the HiPPO framework showing that continuous-time projection operators can be…
Thinking like a CHEMIST: Combined Heterogeneous Embedding Model Integrating Structure and Tokens
Nikolai Rekut, Alexey Orlov, Klea Ziu +3
Representing molecular structures effectively in chemistry remains a challenging task. Language models and graph-based models are extensively utilized within this domain, consisten…
DAG: Projected Stochastic Approximation Iteration for DAG Structure Learning
Klea Ziu, Slavomír Hanzely, Loka Li +3
Learning the structure of Directed Acyclic Graphs (DAGs) presents a significant challenge due to the vast combinatorial search space of possible graphs, which scales exponentially…