PyTorch 2 Model for the prediction of single-artery segmentations for "AngioPy segmentation: An open-source, user-guided deep learning tool for coronary artery segmentation"

About
Privacy
Disclaimer

Graph Chatbot

Related publications (25)

Page 2 of 2

Enhancing multivariate, multi-step residential load forecasting with spatiotemporal graph attention-enabled transformer

Wenlong Liao

Short-term residential load forecasting (STRLF) holds great significance for the stable and economic operation of distributed power systems. Different households in the same region may exhibit similar consumption patterns owing to the analogous environment ...

2024

Modeling the ferroelectric phase transition in barium titanate with DFT accuracy and converged sampling

Michele Ceriotti, Alexander Jan Goscinski, Lorenzo Gigli

The accurate description of the structural and thermodynamic properties of ferroelectrics has been one of the most remarkable achievements of density functional theory (DFT). However, running large simulation cells with DFT is computationally demanding, wh ...

2024

NoiseNCA: Noisy Seed Improves Spatio-Temporal Continuity of Neural Cellular Automata

Sabine Süsstrunk, Ehsan Pajouheshgar, Yitao Xu

Neural Cellular Automata (NCA) is a class of Cellular Automata where the update rule is parameterized by a neural network that can be trained using gradient descent. In this paper, we focus on NCA models used for texture synthesis, where the update rule is ...

MIT Press2024

Fast Streaming Transducer ASR Prototyping via Knowledge Distillation with Whisper

Juan Pablo Zuluaga Gomez

The training of automatic speech recognition (ASR) with little to no supervised data remains an open question. In this work, we demonstrate that streaming Transformer-Transducer (TT) models can be trained from scratch in consumer and accessible GPUs in the ...

Association for Computational Linguistics (ACL)2024

Integrating symmetry and physical constraints into atomic-scale machine learning

Jigyasa Nigam

Over the past decade, computational atomistic modeling, driven by machine learning (ML), has become indispensable to scientific endeavors, improving our understanding and accelerating the search for compounds with enhanced properties. Traditional atomistic ...

EPFL2024