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Machine Learning
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The newest 5,000 papers, from 12 October 2026 to 5 November 2026: 5,000 arXiv preprints.
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Newest papers, page 71
Hidden Phase Transition in Single-Polymer Stretching under Elongational Flow
Using machine learning, we identify a second transition in polymer chain stretching driven by planar elongational flow, beyond the well-known coil-stretch transition.Learning Kolmogorov Backward Operators for Spectral Analysis and Forecasting: A Data-Driven Variational Galerkin Framework
For a time-homogeneous Markov process, the fixed-lag solution operator \( (T_τf)(x)=\mathbb E[f(X_{t+τ})\mid X_t=x] \) of the Kolmogorov backward equation evolves observables linearly and…Improving the Intrinsic Interpretability of Differentiable Decision Trees through Euclidean Feature-Concentration Regularisation
Differentiable decision trees (DDTs) support end-to-end optimisation and explicit decision paths, but dense oblique splits can obscure the role of individual input features.Carbon-Aware Electric Vehicle Routing Problem with Decision-Focused Learning
Electric vehicles produce no tailpipe emissions, but charging them produces emissions that depend on the time-varying generation mix of the electricity consumed.A New AFIB Detection Method with Deep Neural Networks
Early detection of atrial fibrillation (AFIB), characterized by irregular heart rhythms, can potentially save thousands of lives annually [20].Formalizing the Intrinsic Dimension of Objective Landscapes by a Generalized Notion of Co-dimension
In this work, we formalize the concept of intrinsic dimension of objective landscapes introduced in Li et al. (2018), which measures the structural complexity of learning problems by training along…Event-SAMA: Language-Grounded Video Object Segmentation on Neuromorphic Event Streams
Event cameras offer microsecond temporal resolution, high dynamic range and no motion blur, but referring video object segmentation (RVOS) lacks event-stream datasets and models.Heterogeneous Co-Evolution Learning for Tool-Efficient Search Agents with Zero Labels
Deep search agents extend language models by interleaving reasoning with external retrieval.Transformer-inspired architectures make machine-learned electron densities accurate and transferable enough to bypass self-consistency
We introduce machine learning models that accurately predict the electron density, the central variable of density functional theory.Smartphone Indoor Localization Enhanced by Hierarchical Multi-Sensor Context Recognition
Smartphone indoor localization requires low-cost, robust positioning across scene transitions and phone-use variations.Bayes-Consistent Losses for Adaptive Inference in Classification
Adaptive inference systems balance accuracy and inference cost by routing inputs to models with varying capabilities.Sandman: A Sandbox Service for Production Agentic Reinforcement Learning
Agentic reinforcement learning (RL) needs stateful environments for tool execution and evaluation.Adaptive Federated Optimization Across Smooth and Nonsmooth Regimes
AdaGrad-style methods can simultaneously adapt to both the order and constants of smoothness in centralized optimization.Implicit Bias of (Stochastic) Gradient Descent on Deep Linear Diagonal Networks
Modern machine learning models are often overparameterized, i.e., have more parameters than training data.Grounding Predictive Reliability through Masked Observability
An uncertainty estimate is meaningful only if its semantics can be tied to observable predictive behavior.Going deep, reaching further: What can Boltzmann machines efficiently represent?
While universal approximation theorems theoretically underpin the representation capabilities of machine learning models, they have two shortcomings: They do not focus on efficient representations…Activation Probes Are Reliable With a Handful of Positive Examples
Efforts to monitor advanced AI for rare misalignments face a data challenge: abundant aligned examples but only a handful of misaligned ones.Multi-output LSTM soft sensors for industrial anaerobic co-digestion using LSTM-beta-VAE generative data augmentation
Anaerobic digestion (AD) requires close monitoring of key process variables, including pH, the ratio of volatile organic acids to alkaline buffer capacity and biogas production, to maintain…Quantum-Inspired Convolutional Networks for High-Resolution Pseudo-Label Generation from Multimodal Earth Observation Data
Accurate land-cover mapping from multimodal Earth observation (EO) data remains a challenge in regions where high-resolution annotations are scarce or costly to obtain.Surface Conditioning for Zero-Shot Multivariate Correction in a Marine Biogeochemistry Emulator
Bias correction in process-based models usually means iterative data assimilation with explicit covariance modelling.