arXiv:2511.01938v1 Announce Type: new Abstract: Grokking is a puzzling phenomenon in neural networks where full generalization occurs only after a substantial delay following the complete memorization of the training data. Previous research has linked this delayed generalization to representation learning…
arXiv:2506.02935v4 Announce Type: replace Abstract: Multi-Task Learning (MTL) in Neural Combinatorial Optimization (NCO) is a promising approach to train a unified model capable of solving multiple Vehicle Routing Problem (VRP) variants. However, existing Reinforcement Learning (RL)-based multi-task methods can only…
arXiv:2511.01945v1 Announce Type: new Abstract: Amyotrophic lateral sclerosis (ALS) is a severe disease with a typical survival of 3-5 years after symptom onset. Current treatments offer only limited life extension, and the variability in patient responses highlights the need for…
arXiv:2509.01486v2 Announce Type: replace Abstract: Structure-based drug design (SBDD), aiming to generate 3D molecules with high binding affinity toward target proteins, is a vital approach in novel drug discovery. Although recent generative models have shown great potential, they suffer from…
arXiv:2511.01946v1 Announce Type: new Abstract: Covalent organic frameworks (COFs) are promising adsorbents for gas adsorption and separation, while identifying the optimal structures among their vast design space requires efficient high-throughput screening. Conventional machine-learning predictors rely heavily on specific gas-related features.…
arXiv:2510.25557v2 Announce Type: replace Abstract: We present a hybrid quantum-classical recurrent neural network (QRNN) architecture in which the recurrent core is realized as a parametrized quantum circuit (PQC) controlled by a classical feedforward network. The hidden state is the quantum…
arXiv:2511.01947v1 Announce Type: new Abstract: Cardiovascular disease (CVD) remains a critical global health concern, demanding reliable and interpretable predictive models for early risk assessment. This study presents a large-scale analysis using the Heart Disease Health Indicators Dataset, developing a strategically…
arXiv:2406.18613v3 Announce Type: replace-cross Abstract: Let $C_h$ be a composition operator mapping $L^2(Omega_1)$ into $L^2(Omega_2)$ for some open sets $Omega_1, Omega_2 subseteq mathbb{R}^n$. We characterize the mappings $h$ that transform Riesz bases of $L^2(Omega_1)$ into Riesz bases of $L^2(Omega_2)$. Restricting…
arXiv:2511.01950v1 Announce Type: new Abstract: Standard Recurrent Neural Networks, including LSTMs, struggle to model long-range dependencies, particularly in sequences containing noisy or misleading information. We propose a new architectural principle, Output-Conditioned Gating, which enables a model to perform self-reflection by…
arXiv:2503.20000v2 Announce Type: replace-cross Abstract: Coral reefs are declining worldwide due to climate change and local stressors. To inform effective conservation or restoration, monitoring at the highest possible spatial and temporal resolution is necessary. Conventional coral reef surveying methods are…
