250 citations · 532 across the 72 of their papers we have counts for
12 papers · 1 filter
ETAGE: Enhanced Test Time Adaptation with Integrated Entropy and Gradient Norms for Robust Model Performance
Afshar Shamsi, Rejisa Becirovic, Ahmadreza Argha +3
Test time adaptation (TTA) equips deep learning models to handle unseen test data that deviates from the training distribution, even when source data is inaccessible. While traditi…
InvariantStock: Learning Invariant Features for Mastering the Shifting Market
Haiyao Cao, Jinan Zou, Yuhang Liu +4
Accurately predicting stock returns is crucial for effective portfolio management. However, existing methods often overlook a fundamental issue in the market, namely, distribution…
Rethinking State Disentanglement in Causal Reinforcement Learning
Haiyao Cao, Zhen Zhang, Panpan Cai +7
One of the significant challenges in reinforcement learning (RL) when dealing with noise is estimating latent states from observations. Causality provides rigorous theoretical supp…
On the Credibility of Backdoor Attacks Against Object Detectors in the Physical World
Bao Gia Doan, Dang Quang Nguyen, Callum Lindquist +7
Object detectors are vulnerable to backdoor attacks. In contrast to classifiers, detectors possess unique characteristics, architecturally and in task execution; often operating in…
Bayesian Low-Rank LeArning (Bella): A Practical Approach to Bayesian Neural Networks
Bao Gia Doan, Afshar Shamsi, Xiao-Yu Guo +6
Computational complexity of Bayesian learning is impeding its adoption in practical, large-scale tasks. Despite demonstrations of significant merits such as improved robustness and…
Knowledge Composition using Task Vectors with Learned Anisotropic Scaling
Frederic Z. Zhang, Paul Albert, Cristian Rodriguez-Opazo +2
Pre-trained models produce strong generic representations that can be adapted via fine-tuning. The learned weight difference relative to the pre-trained model, known as a task vect…