Revision History for Geometry|enhanced pretraining on...

Revision History for Geometry-enhanced pretraining on...

Revision History for Geometry-enhanced pretraining on... · Edit Edit by Uploader · Edit Info · Record Edit by Taoyong Cui · Edit Info ...

Geometry-enhanced Pre-training on Interatomic Potentials - arXiv

Physics > Chemical Physics. arXiv:2309.15718 (physics). [Submitted on 27 Sep 2023 (v1), last revised 13 Apr 2024 (this version, v3)] ...

Geometry-enhanced Pre-training on Interatomic Potentials - arXiv

Machine learning for molecular simulation. Annual review of physical chemistry 71, 361–390 (2020). [9] ↑ Unke ...

GPIP: Geometry-enhanced Pre-training on Interatomic Potentials

The experimental results show that the proposed pre-training method can greatly enhance the accuracy of MLIPs with few extra computational costs and works well ...

GPIP: Geometry-enhanced Pre-training on Interatomic Potentials

Version of Record: A version of this preprint was published at Nature Machine Intelligence on April 5th,. 2024. See the published version at ...

Revision History for Molecular Geometry Pretraining ... - OpenReview

Revision History for Molecular Geometry Pretraining with... Compare Revisions ... Molecular Geometry Pretraining with SE(3)-Invariant Denoising Distance Matching ...

Molecular Geometry Pretraining with SE(3)-Invariant Denoising ...

The log files and checkpoints for other baselines will be released in the next version. Cite us. Feel free to cite this work if you find it useful to you! @ ...

HOP+: History-Enhanced and Order-Aware Pre-Training for Vision ...

Recent works attempt to employ pre-training in Vision-and-Language Navigation (VLN). However, these methods neglect the importance of ...

Geometry-enhanced molecular representation learning for property ...

Existing works that apply pre-training methods for molecular property prediction fail to utilize the molecular geometries described by bonds, ...

A Systematic Survey of Chemical Pre-trained Models [IJCAI 2023]

[ICLR 2023]Mole-BERT: Rethinking Pre-training Graph Neural Networks for Molecules[paper][code]; [ICLR 2023]Molecular Geometry Pretraining ...

Pre-trained models: Past, present and future - ScienceDirect.com

In this paper, we take a deep look into the history of pre-training, especially its special relation with transfer learning and self-supervised learning.

A Knowledge-Enhanced Pretraining Model for Commonsense Story ...

Article history. Received: October 01 2019. Revision Received: November 01 2019. Cite Icon Cite. Open the PDF for in another window.

COMPRER: A Multimodal Multi-Objective Pretraining Framework for ...

COMPRER: A Multimodal Multi-Objective Pretraining Framework for Enhanced Medical Image Representation ... Info/History; Metrics; Data/Code ...

Pre-training Enhanced Spatial-temporal Graph Neural Network for ...

We design a pre-training model to efficiently learn temporal patterns from very long-term history time series (eg, the past two weeks) and generate segment- ...

A Group Symmetric Stochastic Differential Equation Model for ...

Meanwhile, existing molecule multi- modal pretraining approaches approximate MI based on the representation space encoded from the topology and geometry, thus ...

A survey of the impact of self-supervised pretraining for diagnostic ...

The results of this review overwhelmingly suggest that pretraining with self ... Boundary-Enhanced Self-supervised Learning for Brain Structure Segmentation.

MM-Retinal: Knowledge-Enhanced Foundational Pretraining with ...

Current version of MM-Retinal dataset includes 2,169 CFP cases, 1,947 FFA cases and 233 OCT cases. Each case is provided with an image and texts in both.

Pre-training Molecular Graph Representations with Motif-Enhanced ...

Recently, molecular representation learning (MRL) based on graph neural networks (GNNs) has flourished. Many existing approaches are purely data-driven, ...

XLNet: Enhanced NLP with Generalized Autoregressive Pretraining

... version of the input sequence, where some tokens are masked. The ... history, providing a more accurate and helpful answer. 2. Text ...

Pretraining Strategies for Structure Agnostic Material Property ...

Publication History. Received. 20 June 2023. Accepted. 12 January 2024. Revised ... enhanced model effectiveness, especially in the context of ...