8 citations · 8 across the 15 of their papers we have counts for
10 papers · 1 filter
ARCADE: Adaptive Robot Control with Online Changepoint-Aware Bayesian Dynamics Learning
Rishabh Dev Yadav, Avirup Das, Hongyu Song +2
Real-world robots must operate under evolving dynamics caused by changing operating conditions, external disturbances, and unmodeled effects. These may appear as gradual drifts, tr…
Softly Constrained Denoisers for Diffusion Models Applied to Partial Differential Equations
Victor M. Yeom-Song, Severi Rissanen, Arno Solin +2
Diffusion models have become a powerful generative prior for solutions of partial differential equations (PDEs). Existing approaches enforce physical constraints either by adding t…
More Than Irrational: Modeling Belief-Biased Agents
Yifan Zhu, Sammie Katt, Samuel Kaski
Despite the explosive growth of AI and the technologies built upon it, predicting and inferring the sub-optimal behavior of users or human collaborators remains a critical challeng…
A Principle of Targeted Intervention for Multi-Agent Reinforcement Learning
Anjie Liu, Jianhong Wang, Samuel Kaski +2
Steering cooperative multi-agent reinforcement learning (MARL) towards desired outcomes is challenging, particularly when the global guidance from a human on the whole multi-agent…
Attentive Convolution: Unifying the Expressivity of Self-Attention with Convolutional Efficiency
Hao Yu, Haoyu Chen, Yan Jiang +4
Self-attention (SA) has become the cornerstone of modern vision backbones for its powerful expressivity over traditional Convolutions (Conv). However, its quadratic complexity rema…
Rethinking Inter-LoRA Orthogonality in Adapter Merging: Insights from Orthogonal Monte Carlo Dropout
Andi Zhang, Xuan Ding, Haofan Wang +2
We propose Orthogonal Monte Carlo Dropout, a mechanism that enforces strict orthogonality when combining sparse semantic vectors without extra time complexity. Low-Rank Adaptation…
An Interactive Framework for Finding the Optimal Trade-off in Differential Privacy
Yaohong Yang, Aki Rehn, Sammie Katt +2
Differential privacy (DP) is the standard for privacy-preserving analysis, and introduces a fundamental trade-off between privacy guarantees and model performance. Selecting the op…
Virtual Laboratories: Domain-agnostic workflows for research
Carlos Sevilla-Salcedo, Armi Tiihonen, Mahsa Asadi +4
Many scientific disciplines have traditionally advanced by iterating over hypotheses using labor-intensive trial-and-error, which is a slow and expensive process. Recent advances i…
Concept-based Adversarial Attack: a Probabilistic Perspective
Andi Zhang, Xuan Ding, Steven McDonagh +1
We propose a concept-based adversarial attack framework that extends beyond single-image perturbations by adopting a probabilistic perspective. Rather than modifying a single image…
Shapley Machine: A Game-Theoretic Framework for N-Agent Ad Hoc Teamwork
Jianhong Wang, Yang Li, Samuel Kaski +1
Open multi-agent systems are increasingly important in modeling real-world applications, such as smart grids, swarm robotics, etc. In this paper, we aim to investigate a recently p…