:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Li, Xuyang, Maulik, Romit
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2502.15512
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

A Weak Penalty Neural ODE for Learning Chaotic Dynamics from Noisy Time Series
by: Li, Xuyang, et al.
Published: (2025)

Interpretable Diagnostics and Adaptive Data Assimilation for Neural ODEs via Discrete Empirical Interpolation
by: Kim, Hojin, et al.
Published: (2025)

Leveraging Interpolation Models and Error Bounds for Verifiable Scientific Machine Learning
by: Chang, Tyler, et al.
Published: (2024)

A competitive baseline for deep learning enhanced data assimilation using conditional Gaussian ensemble Kalman filtering
by: Malik, Zachariah, et al.
Published: (2024)

Higher order quantum reservoir computing for non-intrusive reduced-order models
by: Jain, Vinamr, et al.
Published: (2024)

SC3D: Dynamic and Differentiable Causal Discovery for Temporal and Instantaneous Graphs
by: Das, Sourajit, et al.
Published: (2026)

Deep Learning of Solver-Aware Turbulence Closures from Nudged LES Dynamics
by: Suriyanarayanan, Ashwin, et al.
Published: (2026)

FIGNN: Feature-Specific Interpretability for Graph Neural Network Surrogate Models
by: Raut, Riddhiman, et al.
Published: (2025)

Binned Spectral Power Loss for Improved Prediction of Chaotic Systems
by: Chakraborty, Dibyajyoti, et al.
Published: (2025)

Adaptive Diffusion Posterior Sampling for Data and Model Fusion of Complex Nonlinear Dynamical Systems
by: Chakraborty, Dibyajyoti, et al.
Published: (2026)

Interpretable A-posteriori Error Indication for Graph Neural Network Surrogate Models
by: Barwey, Shivam, et al.
Published: (2023)

Semi-Implicit Neural Ordinary Differential Equations
by: Zhang, Hong, et al.
Published: (2024)

Divide And Conquer: Learning Chaotic Dynamical Systems With Multistep Penalty Neural Ordinary Differential Equations
by: Chakraborty, Dibyajyoti, et al.
Published: (2024)

Generalizable data-driven turbulence closure modeling on unstructured grids with differentiable physics
by: Kim, Hojin, et al.
Published: (2023)

Differentiable Turbulence: Closure as a partial differential equation constrained optimization
by: Shankar, Varun, et al.
Published: (2023)

Localized PCA-Net Neural Operators for Scalable Solution Reconstruction of Elliptic PDEs
by: Dhingra, Mrigank, et al.
Published: (2025)

A note on the error analysis of data-driven closure models for large eddy simulations of turbulence
by: Chakraborty, Dibyajyoti, et al.
Published: (2024)

LUCIE-3D: A three-dimensional climate emulator for forced responses
by: Guan, Haiwen, et al.
Published: (2025)

LUCIE: A Lightweight Uncoupled ClImate Emulator with long-term stability and physical consistency for O(1000)-member ensembles
by: Guan, Haiwen, et al.
Published: (2024)

Measure-Theoretic Time-Delay Embedding
by: Botvinick-Greenhouse, Jonah, et al.
Published: (2024)

Improved deep learning of chaotic dynamical systems with multistep penalty losses
by: Chakraborty, Dibyajyoti, et al.
Published: (2024)

Robust experimental data assimilation for the Spalart-Allmaras turbulence model
by: Aulakh, Deepinder Jot Singh, et al.
Published: (2023)

High-Resolution Climate Projections Using Diffusion-Based Downscaling of a Lightweight Climate Emulator
by: Guan, Haiwen, et al.
Published: (2026)

Multimodal Atmospheric Super-Resolution With Deep Generative Models
by: Chakraborty, Dibyajyoti, et al.
Published: (2025)

Taming OOD Actions for Offline Reinforcement Learning: An Advantage-Based Approach
by: Chen, Xuyang, et al.
Published: (2025)

SALSA: Soup-based Alignment Learning for Stronger Adaptation in RLHF
by: Chegini, Atoosa, et al.
Published: (2024)

Enhancing Machine Learning Model Efficiency through Quantization and Bit Depth Optimization: A Performance Analysis on Healthcare Data
by: Goswami, Mitul, et al.
Published: (2025)

SLAC: Simulation-Pretrained Latent Action Space for Whole-Body Real-World RL
by: Hu, Jiaheng, et al.
Published: (2025)

Data-Driven Physics-Informed Neural Networks: A Digital Twin Perspective
by: Yang, Sunwoong, et al.
Published: (2024)

RL-Obfuscation: Can Language Models Learn to Evade Latent-Space Monitors?
by: Gupta, Rohan, et al.
Published: (2025)

SALSA: Single-pass Autoregressive LLM Structured Classification
by: Berdichevsky, Ruslan, et al.
Published: (2025)

Latent Spherical Flow Policy for Reinforcement Learning with Combinatorial Actions
by: Kong, Lingkai, et al.
Published: (2026)

MoWE : A Mixture of Weather Experts
by: Chakraborty, Dibyajyoti, et al.
Published: (2025)

Evaluating the Stability of Deep Learning Latent Feature Spaces
by: Mabadeje, Ademide O., et al.
Published: (2024)

Global Optimality of Single-Timescale Actor-Critic under Continuous State-Action Space: A Study on Linear Quadratic Regulator
by: Chen, Xuyang, et al.
Published: (2025)

HIQL: Offline Goal-Conditioned RL with Latent States as Actions
by: Park, Seohong, et al.
Published: (2023)

SALSA: Speedy ASR-LLM Synchronous Aggregation
by: Mittal, Ashish, et al.
Published: (2024)

An Investigation of Offline Reinforcement Learning in Factorisable Action Spaces
by: Beeson, Alex, et al.
Published: (2024)

Learning Energy-based Variational Latent Prior for VAEs
by: Dutta, Debottam, et al.
Published: (2025)

In-Context Reinforcement Learning for Variable Action Spaces
by: Sinii, Viacheslav, et al.
Published: (2023)