An Efficient and Explainable Transformer-Based Few-Shot Learning for
Modeling Electricity Consumption Profiles Across Thousands of Domains

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An Efficient and Explainable Transformer-Based Few-Shot Learning for Modeling Electricity Consumption Profiles Across Thousands of Domains

15 August 2024

Pedro P. Vergara

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Papers citing "An Efficient and Explainable Transformer-Based Few-Shot Learning for Modeling Electricity Consumption Profiles Across Thousands of Domains"

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Title
CSDI: Conditional Score-based Diffusion Models for Probabilistic Time Series Imputation Y. Tashiro Jiaming Song Yang Song Stefano Ermon BDL DiffM 57 544 0 07 Jul 2021
Few-shot Image Generation via Cross-domain Correspondence Utkarsh Ojha Yijun Li Jingwan Lu Alexei A. Efros Yong Jae Lee Eli Shechtman Richard Y. Zhang 115 263 0 13 Apr 2021
Autoregressive Denoising Diffusion Models for Multivariate Probabilistic Time Series Forecasting Kashif Rasul Calvin Seward Ingmar Schuster Roland Vollgraf DiffM 105 320 0 28 Jan 2021
Few-shot Image Generation with Elastic Weight Consolidation Yijun Li Richard Y. Zhang Jingwan Lu Eli Shechtman 3DH 94 169 0 04 Dec 2020
Meta-Baseline: Exploring Simple Meta-Learning for Few-Shot Learning Yinbo Chen Zhuang Liu Huijuan Xu Trevor Darrell Xiaolong Wang 209 347 0 09 Mar 2020
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding Jacob Devlin Ming-Wei Chang Kenton Lee Kristina Toutanova VLM SSL SSeg 1.8K 95,175 0 11 Oct 2018
AffinityNet: semi-supervised few-shot learning for disease type prediction Tianle Ma A. Zhang 67 55 0 22 May 2018
Learning feed-forward one-shot learners Luca Bertinetto João F. Henriques Jack Valmadre Philip Torr Andrea Vedaldi 72 471 0 16 Jun 2016
Cyclical Learning Rates for Training Neural Networks L. Smith ODL 233 2,537 0 03 Jun 2015