Cover Image

A fully differentiable framework for training proxy Exchange Correlation Functionals for periodic systems

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Singh, Rakshit Kumar, Barsainyan, Aryan Amit, Ramsundar, Bharath
Format:	Preprint
Published:	2026
Subjects:	Materials Science Artificial Intelligence Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Deepmechanics
by: Shinde, Abhay, et al.
Published: (2026)

STORI: A Benchmark and Taxonomy for Stochastic Environments
by: Barsainyan, Aryan Amit, et al.
Published: (2025)

Open-Source Molecular Processing Pipeline for Generating Molecules
by: Shreyas, V, et al.
Published: (2024)

Machine Learning - Driven Materials Discovery: Unlocking Next-Generation Functional Materials - A review
by: Nematov, Dilshod, et al.
Published: (2025)

MEIDNet: Multimodal generative AI framework for inverse materials design
by: Babu, Anand, et al.
Published: (2026)

LEAP: A closed-loop framework for perovskite precursor additive discovery
by: Wang, Xin-De, et al.
Published: (2026)

Open source Differentiable ODE Solving Infrastructure
by: Singh, Rakshit Kr., et al.
Published: (2024)

Prakriti200: A Questionnaire-Based Dataset of 200 Ayurvedic Prakriti Assessments
by: Singh, Aryan Kumar, et al.
Published: (2025)

SpectraFormer: an Attention-Based Raman Unmixing Tool for Accessing the Graphene Buffer-Layer Signature on SiC
by: Poteryayev, Dmitriy, et al.
Published: (2026)

Can LLMs Predict Polymer Physics Just by Reading Synthesis and Processing Prose?
by: Liu, Yuchu, et al.
Published: (2026)

AI Meets Plasticity: A Comprehensive Survey
by: Bakhshan, Hadi, et al.
Published: (2026)

The Infinite-Dimensional Nature of Spectroscopy and Why Models Succeed, Fail, and Mislead
by: Michelucci, Umberto, et al.
Published: (2026)

Zatom-1: Towards a Multimodal Foundation Model for 3D Molecules and Materials
by: Morehead, Alex, et al.
Published: (2026)

Constrained Diffusion for Accelerated Structure Relaxation of Inorganic Solids with Point Defects
by: Cui, Jingyi, et al.
Published: (2026)

What drives performance in molecular MPNNs? An operator-level factorial benchmark
by: Jiao, Panyu, et al.
Published: (2026)

Performance of AI agents based on reasoning language models on ALD process optimization tasks
by: Yanguas-Gil, Angel
Published: (2026)

AI scientists produce results without reasoning scientifically
by: Ríos-García, Martiño, et al.
Published: (2026)

Meta-LegNet: A Transferable and Interpretable Framework for Surface Adsorption Prediction via Self-Defined Adsorption-Environment Learning
by: Li, Yifan, et al.
Published: (2026)

Supervised Pretraining for Material Property Prediction
by: Rahman, Chowdhury Mohammad Abid, et al.
Published: (2025)

OmniXAS: A Universal Deep-Learning Framework for Materials X-ray Absorption Spectra
by: Kharel, Shubha R., et al.
Published: (2024)

LLM Meets Diffusion: A Hybrid Framework for Crystal Material Generation
by: Khastagir, Subhojyoti, et al.
Published: (2025)

Benchmarking large language models for materials synthesis: the case of atomic layer deposition
by: Yanguas-Gil, Angel, et al.
Published: (2024)

Machine Learned Force Fields: Fundamentals, its reach, and challenges
by: Vital, Carlos A., et al.
Published: (2025)

XxaCT-NN: Structure Agnostic Multimodal Learning for Materials Science
by: Subramanian, Jithendaraa, et al.
Published: (2025)

Energy & Force Regression on DFT Trajectories is Not Enough for Universal Machine Learning Interatomic Potentials
by: Miret, Santiago, et al.
Published: (2025)

EGMOF: Efficient Generation of Metal-Organic Frameworks Using a Hybrid Diffusion-Transformer Architecture
by: Han, Seunghee, et al.
Published: (2025)

FlowLLM: Flow Matching for Material Generation with Large Language Models as Base Distributions
by: Sriram, Anuroop, et al.
Published: (2024)

WyckoffDiff -- A Generative Diffusion Model for Crystal Symmetry
by: Kelvinius, Filip Ekström, et al.
Published: (2025)

CAST: Cross Attention based multimodal fusion of Structure and Text for materials property prediction
by: Lee, Jaewan, et al.
Published: (2025)

Tensor Completion for Surrogate Modeling of Material Property Prediction
by: Pakala, Shaan, et al.
Published: (2025)

LLM-Fusion: A Novel Multimodal Fusion Model for Accelerated Material Discovery
by: Boyar, Onur, et al.
Published: (2025)

MechProNet: Machine Learning Prediction of Mechanical Properties in Metal Additive Manufacturing
by: Akbari, Parand, et al.
Published: (2022)

Molecular topological deep learning for polymer property prediction
by: Shen, Cong, et al.
Published: (2024)

Autonomous Multi-objective Alloy Design through Simulation-guided Optimization
by: Yang, Penghui, et al.
Published: (2025)

MatterTune: An Integrated, User-Friendly Platform for Fine-Tuning Atomistic Foundation Models to Accelerate Materials Simulation and Discovery
by: Kong, Lingyu, et al.
Published: (2025)

Interaction Topological Transformer for Multiscale Learning in Porous Materials
by: Chen, Dong, et al.
Published: (2025)

Steering an Active Learning Workflow Towards Novel Materials Discovery via Queue Prioritization
by: Schwarting, Marcus, et al.
Published: (2025)

PolySet: Restoring the Statistical Ensemble Nature of Polymers for Machine Learning
by: Ferji, Khalid
Published: (2025)

MOFGPT: Generative Design of Metal-Organic Frameworks using Language Models
by: Badrinarayanan, Srivathsan, et al.
Published: (2025)

Beyond designer's knowledge: Generating materials design hypotheses via large language models
by: Liu, Quanliang, et al.
Published: (2024)