Cover Image

Mollifier Layers: Enabling Efficient High-Order Derivatives in Inverse PDE Learning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Bhartari, Ananyae Kumar, Vinayak, Vinayak, Shenoy, Vivek B
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Gradient Alignment in Physics-informed Neural Networks: A Second-Order Optimization Perspective
by: Wang, Sifan, et al.
Published: (2025)

Sub-Diffraction Chromatin Domains: Architecture, Regulation, and Functional Roles in Nuclear Organization
by: Vinayak, Vinayak, et al.
Published: (2025)

Mollified Value Learning
by: Viswanath, Hrishikesh, et al.
Published: (2026)

Enabling Automatic Differentiation with Mollified Graph Neural Operators
by: Lin, Ryan Y., et al.
Published: (2025)

Thresholded Lexicographic Ordered Multiobjective Reinforcement Learning
by: Tercan, Alperen, et al.
Published: (2024)

Simplifying Adversarially Robust PAC Learning with Tolerance
by: Ashtiani, Hassan, et al.
Published: (2025)

Metric Learning from Limited Pairwise Preference Comparisons
by: Wang, Zhi, et al.
Published: (2024)

Bridging Lifelong and Multi-Task Representation Learning via Algorithm and Complexity Measure
by: Wang, Zhi, et al.
Published: (2025)

Efficient and Responsible Adaptation of Large Language Models for Robust and Equitable Top-k Recommendations
by: Kaur, Kirandeep, et al.
Published: (2025)

Scaling Equilibrium Propagation to Deeper Neural Network Architectures
by: Elayedam, Sankar Vinayak, et al.
Published: (2025)

Neural Diffusion Intensity Models for Point Process Data
by: Du, Xinlong, et al.
Published: (2026)

PAL: Pluralistic Alignment Framework for Learning from Heterogeneous Preferences
by: Chen, Daiwei, et al.
Published: (2024)

Offline Estimation of Controlled Markov Chains: Minimaxity and Sample Complexity
by: Banerjee, Imon, et al.
Published: (2022)

Total Uncertainty Quantification in Inverse PDE Solutions Obtained with Reduced-Order Deep Learning Surrogate Models
by: Wang, Yuanzhe, et al.
Published: (2024)

PROPER Agents: Proactivity Driven Personalized Agents for Advancing Knowledge Gap Navigation
by: Kaur, Kirandeep, et al.
Published: (2026)

Adaptive Scoring and Thresholding with Human Feedback for Robust Out-of-Distribution Detection
by: Yamada, Daisuke, et al.
Published: (2025)

Taming False Positives in Out-of-Distribution Detection with Human Feedback
by: Vishwakarma, Harit, et al.
Published: (2024)

Metric Learning in an RKHS
by: Tatli, Gokcan, et al.
Published: (2025)

Can Large Language Models Unlock Novel Scientific Research Ideas?
by: Kumar, Sandeep, et al.
Published: (2024)

$\infty$-Diff: Infinite Resolution Diffusion with Subsampled Mollified States
by: Bond-Taylor, Sam, et al.
Published: (2023)

QLENS: Towards A Quantum Perspective of Language Transformers
by: Gupta, Aditya, et al.
Published: (2025)

An Inverse Scattering Inspired Fourier Neural Operator for Time-Dependent PDE Learning
by: Yu, Rixin
Published: (2025)

Machine Learning Models for Reinforced Concrete Pipes Condition Prediction: The State-of-the-Art Using Artificial Neural Networks and Multiple Linear Regression in a Wisconsin Case Study
by: Mohammadagha, Mohsen, et al.
Published: (2025)

Promises and Pitfalls of Threshold-based Auto-labeling
by: Vishwakarma, Harit, et al.
Published: (2022)

SPML: A DSL for Defending Language Models Against Prompt Attacks
by: Sharma, Reshabh K, et al.
Published: (2024)

Inverse Evolution Data Augmentation for Neural PDE Solvers
by: Liu, Chaoyu, et al.
Published: (2025)

Agent Ideate: A Framework for Product Idea Generation from Patents Using Agentic AI
by: Kanumolu, Gopichand, et al.
Published: (2025)

Synergistic Learning with Multi-Task DeepONet for Efficient PDE Problem Solving
by: Kumar, Varun, et al.
Published: (2024)

Graph Neural Regularizers for PDE Inverse Problems
by: Lauga, William, et al.
Published: (2025)

Bayesian Physics-Informed Extreme Learning Machine for Forward and Inverse PDE Problems with Noisy Data
by: Liu, Xu, et al.
Published: (2022)

Multi-Agent Inverse Q-Learning from Demonstrations
by: Haynam, Nathaniel, et al.
Published: (2025)

Differentiable Adversarial Attacks for Marked Temporal Point Processes
by: Chakraborty, Pritish, et al.
Published: (2025)

Comprehensive Study Of Predictive Maintenance In Industries Using Classification Models And LSTM Model
by: Maheshwari, Saket, et al.
Published: (2024)

Are Language Models Actually Useful for Time Series Forecasting?
by: Tan, Mingtian, et al.
Published: (2024)

Accelerating PDE-Constrained Optimization by the Derivative of Neural Operators
by: Cheng, Ze, et al.
Published: (2025)

Learning Rate Should Scale Inversely with High-Order Data Moments in High-Dimensional Online Independent Component Analysis
by: Gultekin, M. Oguzhan, et al.
Published: (2025)

Unlearning Noise in PINNs: A Selective Pruning Framework for PDE Inverse Problems
by: Chen, Yongsheng, et al.
Published: (2026)

Taming the Tail: NoI Topology Synthesis for Mixed DL Workloads on Chiplet-Based Accelerators
by: Shukla, Arnav, et al.
Published: (2025)

MetaSynth: Meta-Prompting-Driven Agentic Scaffolds for Diverse Synthetic Data Generation
by: Riaz, Haris, et al.
Published: (2025)

Latent Neural Operator for Solving Forward and Inverse PDE Problems
by: Wang, Tian, et al.
Published: (2024)