Search Results for author:
Found 14 papers, 4 papers with code
Orb: A Fast, Scalable Neural Network Potential
We introduce Orb, a family of universal interatomic potentials for atomistic modelling of materials.
Comparative Analysis of Extrinsic Factors for NER in French
Named entity recognition (NER) is a crucial task that aims to identify structured information, which is often replete with complex, technical terms and a high degree of variability.
Statistical Properties of Robust Satisficing
The Robust Satisficing (RS) model is an emerging approach to robust optimization, offering streamlined procedures and robust generalization across various applications.
Ensuring Disturbance Rejection Performance by Synthesizing Grid-Following and Grid-Forming Inverters in Power Systems
To satisfy dynamic requirements of power systems, it is imperative for grid-tied inverters to ensure good disturbance rejection performance (DRP) under variable grid conditions.
Feynman Diagrams as Computational Graphs
We propose a computational graph representation of high-order Feynman diagrams in Quantum Field Theory (QFT), applicable to any combination of spatial, temporal, momentum, and frequency domains.
Characterizing the Role of Complex Power in Small-Signal Synchronization Stability of Multi-Converter Power Systems
In this paper, we focus on the impact regularity of complex power on the small-signal synchronization stability of the MCPS.
Obj-NeRF: Extract Object NeRFs from Multi-view Images
To solve this problem, in this paper, we propose Obj-NeRF, a comprehensive pipeline that recovers the 3D geometry of a specific object from multi-view images using a single prompt.
Enhancing Energy Efficiency for Reconfigurable Intelligent Surfaces with Practical Power Models
To address this issue, in this paper, we first utilize a practical power model for a RIS-assisted multi-user multiple-input single-output (MU-MISO) communication system, which takes into account the difference in power dissipation caused by ON-OFF states of RIS's PIN diodes.
Towards Foundational Models for Molecular Learning on Large-Scale Multi-Task Datasets
Recently, pre-trained foundation models have enabled significant advancements in multiple fields.
Extrinsic Factors Affecting the Accuracy of Biomedical NER
Biomedical named entity recognition (NER) is a critial task that aims to identify structured information in clinical text, which is often replete with complex, technical terms and a high degree of variability.
PopSparse: Accelerated block sparse matrix multiplication on IPU
Furthermore, static sparsity in general outperforms dynamic sparsity.
GPS++: Reviving the Art of Message Passing for Molecular Property Prediction
We present GPS++, a hybrid Message Passing Neural Network / Graph Transformer model for molecular property prediction.
GPS++: An Optimised Hybrid MPNN/Transformer for Molecular Property Prediction
This technical report presents GPS++, the first-place solution to the Open Graph Benchmark Large-Scale Challenge (OGB-LSC 2022) for the PCQM4Mv2 molecular property prediction task.
Privacy-Preserving Collaborative Operation of Networked Microgrids with the Local Utility Grid Based on Enhanced Benders Decomposition
Abstract—In this paper, a privacy-preserving decision-making the framework is developed for a collaborative operation of networked microgrids and the local utility grid, where the distribution system operator (DSO) interacts with microgrid master controllers (MCs) in a leader-followers fashion.
