NeurIPS 2024 Past Other
NeurIPS 2024 Workshop on Data-driven and Differentiable Simulations, Surrogates, and Solvers
D3S3 2024
- Submission deadline
- Aug 31, 2024, 11:59 UTC imported from OpenReview — check the website for extensions
- Submission portal
- OpenReview
- Notes
- Auto-imported from the OpenReview venue record on 2026-06-10 — please verify and enrich (topics are keyword-guessed).
Accepted papers (38)
Fetched from OpenReview (v2) on 2026-06-10.
-
A neural surrogate solver for radiation transfer
-
Active Learning for Neural PDE Solvers
-
ADAGE-Diff: Two-level adaptive agent based modelling for differentiable policy design
-
Beyond Closure Models: Learning Chaotic-Systems via Physics-Informed Neural Operators
-
BoostMD: Accelerated Molecular Sampling Leveraging ML Force Field Features
-
Convergence Guarantees for Neural Network-Based Hamilton–Jacobi Reachability
-
Convolutional Hierarchical Deep Learning Neural Networks-Tensor Decomposition (C-HiDeNN-TD): a scalable surrogate modeling approach for large-scale physical systems
-
Cost Estimation in Unit Commitment Problems Using Simulation-Based Inference
-
Efficient Probabilistic Modeling of Crystallization at Mesoscopic Scale
-
Fine-Tuned MLP-Mixer Foundation Models as data-driven Numerical Surrogates?
-
From Function to Distribution Modeling: A PAC-Generative Approach to Offline Optimization
-
Generative Modeling and Data Augmentation for Power System Production Simulation
-
Generative Neural Reparameterization for Differentiable PDE-Constrained Optimization
-
GLEAM-AI: Neural Surrogate for Accelerated Epidemic Analytics and Forecasting
-
Gradient of Clifford Neural Networks
-
Guaranteeing Conservation Laws with Projection in Physics-Informed Neural Networks
-
Improving Generalization of Differentiable Simulator Policies with Sharpness-Aware Optimization
-
Learnable Subset Perturbations for Understanding Transcriptional Regulatory Redundancy
-
Learning cure kinetics of frontal polymerization PDEs using differentiable simulations
-
Learning Generative Interactive Environments By Trained Agent Exploration
-
Learning SDE Solutions with Neural Stochastic Flows
-
Model Exploration through Marginal Likelihood Entropy Maximisation
-
Modelling variation in the forward EMG model.
-
Neural Operators as Fast Surrogate Models for the Transmission Loss of Parameterized Sonic Crystals
-
Optimizing the IFMIF-DONES Particle Accelerator with Differentiable Deep Learning Surrogate Models
-
ParaFIND: Parameter Field Inference on Non-uniform Domains using Neural Network
-
Projected Low-Rank Gradient in Diffusion-based Models for Inverse Problems
-
Projected Neural Differential Equations for Power Grid Modeling with Constraints
-
SepONet: Efficient Large-Scale Physics-Informed Operator Learning
-
Spatial Shortcuts in Graph Neural Controlled Differential Equations
-
Stabilizing Reinforcement Learning in Differentiable Simulation of Deformables
-
Surrogate-based Physical Error Correction for Spectroscopy Quantification
-
SWOT-based Simulation of River Discharge with Temporal Graph Neural Networks
-
The Well: a Large-Scale Collection of Diverse Physics Simulations for Machine Learning
-
Using Parametric PINNs for Predicting Internal and External Turbulent Flows
-
VehicleSDF: A 3D generative model for constrained engineering design via surrogate modeling
-
Wave Interpolation Neural Operator: Interpolated Prediction of Electric Fields Across Untrained Wavelengths
-
When Differentiable Programming Meets Spectral PDE Solver