4 citations · 4 across the 2 of their papers we have counts for
3 papers
cs.AI2026
TaskSense: Focusing on What Matters in World Models
SM Mazharul Islam, Manfred Huber
World models for visual control typically learn compact latent states by reconstructing observations, implicitly encouraging representations to preserve information across the enti…
cs.LG2025★ 4 cited
Reducing Label Dependency in Human Activity Recognition with Wearables: From Supervised Learning to Novel Weakly Self-Supervised Approaches
Taoran Sheng, Manfred Huber
Human activity recognition (HAR) using wearable sensors has advanced through various machine learning paradigms, each with inherent trade-offs between performance and labeling requ…
cs.LG2025
Categorical Policies: Multimodal Policy Learning and Exploration in Continuous Control
SM Mazharul Islam, Manfred Huber
A policy in deep reinforcement learning (RL), either deterministic or stochastic, is commonly parameterized as a Gaussian distribution alone, limiting the learned behavior to be un…