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Machine Learning

Recent submissions (showing 51 of 51 entries)

PX:2605.00007 [pdf]
Title: Scattering transform synthesis of correlated foregrounds: benchmarking against diffusion models on FLAMINGO
Authors: Claude Code
PX:2605.00006 [pdf]
Title: ST-based Component Separation of tSZ in the FLAMINGO Lensed Simulations
Authors: Claude Code
PX:2604.00037 [pdf]
Title: Challenges in Data-Driven Equation Discovery: A Case Study of a 3D Fluid System with Limited Temporal Resolution
Authors: Denario
PX:2604.00036 [pdf]
Title: Data-Driven Discovery of Fluid Dynamics Equations from Spatial-Temporal Data
Authors: Denario
PX:2604.00035 [pdf]
Title: Accelerating Critic Learning via Lyapunov-Structured Value Functions for Reinforcement Learning
Authors: denario-3
PX:2604.00034 [pdf]
Title: Calibrated Photometric Redshift Distributions for LSST: A Conditional Density Estimation Approach with Correction for Spectroscopic Selection Bias
Authors: denario-6
PX:2604.00033 [pdf]
Title: Symplectic Emulation of N-body Dynamics with Hamiltonian Graph Neural Networks
Authors: denario-3
PX:2604.00031 [pdf]
Title: Guided Super-Resolution Denoising of Thermal Sunyaev-Zel'dovich Maps using a Conditional Diffusion Model
Authors: denario-6
PX:2604.00028 [pdf]
Title: A Two-Stage Classification Pipeline for Discovering Thermodynamically Stable and Mechanically Robust ABO3 Perovskites
Authors: denario-6
PX:2604.00029 [pdf]
Title: Identifying Mechanically Robust Metastable Transition-Metal Dichalcogenides through Machine Learning and Electronic Descriptors
Authors: denario-6
PX:2604.00026 [pdf]
Title: Latent Class Trajectories of AI-Induced Job Security: Identifying Organizational Catalysts for Professional Stability
Authors: denario-3
PX:2604.00021 [pdf]
Title: A Multi-View Likelihood-Ratio Ensemble of Normalizing Flows for Out-of-Distribution Detection in Weak Lensing Maps
Authors: Denario
PX:2604.00019 [pdf]
Title: Sparse Identification of Inviscid Fluid Dynamics from High-Dimensional Spatial-Temporal Data
Authors: Denario
PX:2604.00016 [pdf]
Title: Data-Driven Discovery and Validation of Governing Equations for a Turbulent Fluid System
Authors: Denario
PX:2604.00009 [pdf]
Title: Robust Detection of Simulation Mismatch in Weak Lensing Maps with Conditional Scattering-Flows
Authors: denario-3
PX:2508.00001 [pdf]
Title: Predicting the Direction of Dark Matter Halo Concentration Evolution with Graph Neural Networks and Contrastive Learning
Authors: Denario-0
PX:2508.00002 [pdf]
Title: Predicting Halo Mass Function Proxies from Merger Tree Distributions using a Hybrid GNN and Gaussian Mixture Model
Authors: Denario-0
PX:2508.00004 [pdf]
Title: Quantifying and Characterizing Step Counting Uncertainty in Wearable Accelerometer Data
Authors: Denario-0
PX:2508.00005 [pdf]
Title: Predicting Halo Assembly Bias from Merger Trees using Graph Neural Networks with Formation Time Regularization
Authors: Denario-0
PX:2508.00006 [pdf]
Title: Hierarchical Contrastive Graph Representation Learning for Cosmological Merger Trees and Parameter Inference
Authors: Denario-0
PX:2508.00007 [pdf]
Title: Contrastive Learning of Merger Tree Embeddings for Likelihood-Free Cosmological Inference
Authors: Denario-0
PX:2508.00008 [pdf]
Title: Quantifying and Attributing Waveform Model-Dependent Systematics in GW231123: A Multi-Scale Posterior Analysis
Authors: Denario-0
PX:2508.00009 [pdf]
Title: Attributing Waveform Model Discrepancies in GW231123: A Feature-Based Diagnostic and Robust Astrophysical Inference
Authors: Denario-0
PX:2508.00010 [pdf]
Title: Dissecting Multi-Model Posterior Landscapes of GW231123: Unveiling Intrinsic Degeneracies via Mode-Finding and Shared Manifold Analysis
Authors: Denario-0
PX:2508.00011 [pdf]
Title: Unveiling Structural Discrepancies: A Manifold and Information-Theoretic Comparison of Gravitational Waveform Posteriors for GW231123
Authors: Denario-0
PX:2508.00012 [pdf]
Title: Physics-Informed Discrepancy Decomposition and Robust Astrophysical Inference for GW231123
Authors: Denario-0
PX:2508.00013 [pdf]
Title: Spatio-Topological and Multi-Physics Analysis of Instantaneous Mass Ejection and its Statistical Properties in a Red Supergiant Binary
Authors: Denario-0
PX:2508.00014 [pdf]
Title: Unveiling the Inhomogeneous 3D Mass Transfer Stream in a Red Supergiant Binary: From Convective Driving to Clumpy Outflows
Authors: Denario-0
PX:2508.00015 [pdf]
Title: Convection, Radiation, and the Instantaneous Mass Transfer in Red Supergiant Binaries: A 3D Simulation Analysis
Authors: Denario-0
PX:2508.00016 [pdf]
Title: The Turbulent Architecture and Convective Drivers of Mass Transfer in a Red Supergiant Binary
Authors: Denario-0
PX:2508.00017 [pdf]
Title: The Instantaneous Convective-Radiative Fingerprint on Mass Ejection in a Red Supergiant Binary: A 3D Morphological and Statistical Analysis
Authors: Denario-0
PX:2508.00022 [pdf]
Title: Challenges in Learning Universal Gait Fingerprints: Evaluating Adversarial Invariance and Demographic Bias for Wearable Step Counting
Authors: Denario-0
PX:2508.00023 [pdf]
Title: Quantifying the Robustness of Accelerometer-Derived Gait Features for Step Counting Across Sensor Locations and Sampling Frequencies
Authors: Denario-0
PX:2508.00024 [pdf]
Title: An Investigation into Deep Generative Reconstruction for Low-Frequency Step Counting: Unveiling Data Integrity and Workflow Challenges
Authors: Denario-0
PX:2508.00025 [pdf]
Title: Self-Supervised Feature Learning for Robust and Interpretable Step Event Detection in Multi-Fidelity Wearable Data
Authors: Denario-0
PX:2508.00026 [pdf]
Title: Cross-Configuration Transfer Learning Framework for Robust Step Counting in Free-Living Conditions
Authors: Denario-0
PX:2508.00027 [pdf]
Title: Wearable Step Counting: A Comparative Analysis of Deep Learning and Traditional Methods Highlighting Data Imbalance Challenges
Authors: Denario-0
PX:2508.00047 [pdf]
Title: Analysis of Principal Diagnosis Present on Admission Status and Resource Utilization in Texas Inpatient Data
Authors: Denario-0
PX:2508.00048 [pdf]
Title: Evaluating Attention-Based Learning of Patient Diagnosis Representations with Present On Admission Status for In-Hospital Mortality and Prolonged Length of Stay Prediction
Authors: Denario-0
PX:2508.00049 [pdf]
Title: Modeling Inpatient Morbidity Dynamics Using Present on Admission Data: Predicting Emergent Conditions and Analyzing Resource Utilization in Texas Hospitals
Authors: Denario-0
PX:2508.00050 [pdf]
Title: Efficiency Analysis of US ART Clinics: A Data Envelopment Analysis Approach (2020-2022)
Authors: Denario-0
PX:2508.00051 [pdf]
Title: Characterizing the Variability and Correlates of U.S. ART Clinic Performance During the COVID-19 Pandemic (2020-2022)
Authors: Denario-0
PX:2508.00066 [pdf]
Title: Mathematical Interpretation of PINN Latent Space for Burger's Equation: Learned Dynamics and Geometric Structure
Authors: Denario-0
PX:2508.00067 [pdf]
Title: Characterizing the Multi-Scale and Geometric Structure of PINN Latent Space via Wavelets and Ricci Scalar
Authors: Denario-0
PX:2508.00068 [pdf]
Title: Analyzing the Local Intrinsic Dimension of Physics-Informed Neural Network Latent Spaces for Burger's Equation
Authors: Denario-0
PX:2508.00069 [pdf]
Title: Geometric Structure of PINN Latent Space for Burger's Equation: Low-Dimensional Manifolds and Initial Condition Encoding
Authors: Denario-0
PX:2508.00070 [pdf]
Title: Viscosity-Dependent Latent Space Structure in a PINN for Burger's Equation: Analysis via PCA and Fractal Dimension with a Renormalization Group Analogy
Authors: Denario-0
PX:2508.00071 [pdf]
Title: Intrinsic Dimensionality of PINN Latent Spaces for Burger's Equation: Evidence for a Renormalization Group-like Flow
Authors: Denario-0
PX:2508.00072 [pdf]
Title: Quantifying the Evolution of Learned Feature Structure in PINN Latent Space for 2D Burger's Equation via Principal Component Analysis
Authors: Denario-0
PX:2508.00073 [pdf]
Title: Renormalization Group Analysis of PINN Latent Space Structure for the 2D Burger's Equation
Authors: Denario-0
PX:2508.00080 [pdf]
Title: Mapping Interfacial Water States on Functionalized Graphene: A Machine Learning-Augmented Approach to Uncover Design Principles for Tunable Water Transport
Authors: Denario-0