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17,191 papers

#machine learning Preprint Open access Oct 2026

Wong--Zakai Convergence and FNO Learning for Stochastic Volterra Equations

This paper studies Wong--Zakai convergence and Fourier neural operator learning for stochastic Volterra integral equations (SVIEs) describing random systems with memory. A Wong--Zakai theorem establishes convergence of pathwise solutions driven by piecewise linear approximations of Brownian motion to the corresponding...

Wonjae Lee, Jiuk Jang, Hyungbin Park · 0 citations
#artificial intelligence Preprint Open access Oct 2026

Beyond Equation Search: Conjecture-Guided Discovery with SCOPE and ClosureBench

Most symbolic regression methods optimize candidate equations, but improving an equation's fit does not establish whether its underlying scientific conjecture should be retained, revised, or rejected. A conjecture may admit multiple mathematical realizations, and similarly accurate equations may imply different explana...

Yuxiao Hu, Qian Li, Ding Wang et al. · 0 citations
#machine learning Preprint Open access Oct 2026

Delay Complexity Dimension: Learning with Delayed and Censored Labels

We study PAC learning of binary classifiers when labels arrive after random delays and are censored beyond an observation window $W$. How many samples does this observation model require? We propose a distribution-dependent answer, the Delay Complexity Dimension (DCD). The DCD combines the VC dimension with the exact l...

Madhava Gaikwad · 0 citations
#machine learning Preprint Open access Oct 2026

An Initial Study of Physiological Markers for Deepfake Speech Detection

Conventional deepfake speech detectors primarily target synthesis artifacts and often degrade under unseen attacks or recording conditions. Human speech, however, contains physiological markers associated with respiration, phonation, and temporal coordination arising from the speech-production system that synthesizers...

Vojt\v{e}ch Stan\v{e}k, Michal Fri\v{c}, Kamil Malinka et al. · 0 citations
#artificial intelligence Preprint Oct 2026

The Agentic Scientist: Orchestrating Coding Agents for Automated Scientific (Co-)Discovery

Modern coding agents are fundamentally reshaping the role of human input for computational research: they write code, launch in silico experiments, analyze their results, and autonomously operate with ever-increasing time horizons. Despite these developments, fully autonomous research agents suffer from a limited ideat...

R. Lange, Luca Grillotti, Yutaro Yamada et al. · 3 citations
#machine learning Preprint Open access Oct 2026

TorchSpin: Differentiable Electron Paramagnetic Resonance Simulation in PyTorch

Interpreting electron paramagnetic resonance (EPR) spectra commonly requires repeated forward simulation and optimization of spin Hamiltonian parameters. Established software provides mature simulation and fitting methods, but these calculations are not generally available as differentiable components within machine-le...

Alec H. Follmer · 0 citations
#machine learning Preprint Oct 2026

Popularity Trajectories and Mixing Patterns of Urban Venues in Two European Cities

Urban venues such as restaurants, shops, bars and parks host the daily life of a city, and their collective rise and fall signals how vibrant a neighbourhood is. The usual assumption is that a venue's fortunes follow its neighbourhood's, so that how wealthy an area is and how many people live there will decide a venue'...

Wang-Ngai Yeung, L. Meegahapola, D. Quercia et al. · 0 citations
#machine learning Preprint Open access Oct 2026

Distinguishing Process Change, Instrument Fault and Data-Path Corruption in Streaming Telemetry: A Reference Implementation and Benchmark

A reading departs from what a monitoring system expects for one of three reasons: the physical process changed, the instrument is failing, or the value was corrupted between the instrument and the software. The three call for different responses and look alike in a single sample. We state the three-cause problem, prove...

Oleksandr Klymenko · 0 citations
#machine learning Preprint Oct 2026

AI-Driven, Timing-Aware Power Optimization

Post-route power recovery changes cell choices under tightly coupled timing, electrical and physical constraints, and the value of each change depends on what it costs to repair its side effects. We propose an AI-driven framework in which a learned model drives both phases of the optimization: it ranks the powerrecover...

Amit Sharma · 0 citations
#machine learning Preprint Oct 2026

Bayesian Causal Forests for Zero-Inflated Continuous Outcomes

This paper proposes Zero-Inflated Continuous Bayesian Causal Forests with Duan's Smearing (ZIC-BCF-Smear), a decoupled two-part nonparametric estimator that fits a Probit BCF on the full sample to model participation and a Gaussian BCF strictly on the active subpopulation to model positive intensity.

H. G. Souto, E. Wang, Igor Shuryak · 0 citations
#machine learning Preprint Oct 2026

Physics-Guided Multi-Fidelity Surrogate Modeling for Natural Supercavity Geometry of an Axisymmetric Conical Cavitator

Natural supercavitation behind conical cavitators generates a vapor-filled envelope that, when sustained over the full body of a high-speed underwater vehicles, reduces hydrodynamic skin-friction drag and enables performance levels unattainable in fully wetted flow. Accurate prediction of maximum cavity length and maxi...

Vinh Pham, V. Nguyen, Warn-Gyu Park · 0 citations
#artificial intelligence Preprint Open access Oct 2026

Following the Flow the Law Requires: Training Voice Agents to Transfer to Unseen Regulated Procedures in Debt Collection

Voice agents built on large language models (LLMs) now handle customer calls, but in regulated applications completing the task is not enough: the agent must follow a conversational flow set by law. In debt collection, it must confirm it is speaking to the debtor before mentioning the debt, identify itself and the cred...

Petmongkon Pornpichitsuwan, Krittin Pachtrachai, Touchapon Kraisingkorn · 0 citations

From tech blogs

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Microsoft Research Blog Nov 3, 2026

Learn the rules: The hacker mindset

Research Manager Mike Walker reflects on a career spanning hacker culture, cybersecurity, and AI, sharing lessons about trust, teamwork, leadership, and why solving difficult problems requires curiosity, judgment, agility—and an understanding of the rules. The post Learn the rules: The hacker mindset appeared first on Microsoft Research.

Google DeepMind Blog Nov 3, 2026

Agentic cheminformatics with Google Antigravity

Learn how Google Antigravity and our Cheminformatics Skills accelerate drug discovery workflows, search compounds, and propose novel rigidified macrocycles.

MIT News · Artificial Intelligence Oct 28, 2026

Making machines that can listen

Professor Paris Smaragdis develops computers with superhuman hearing for applications like speech recognition, music understanding, and environmental monitoring.

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