Leveraging Hypernetworks and Learnable Kernels for Consumer Energy Forecasting Across Diverse Consumer Types | Paper Citation Record

Observation d4c8d0ea-aea6-4fbd-9766-37a557c37552 · outbound

This paper cites Eia projects nearly 50% increase in world energy usage by 2050,.

Leveraging Hypernetworks and Learnable Kernels for Consumer Energy Forecasting Across Diverse Consumer Types Eia projects nearly 50% increase in world energy usage by 2050,

Reference 1

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This paper cites (2022) 2030 climate & energy framework.

Leveraging Hypernetworks and Learnable Kernels for Consumer Energy Forecasting Across Diverse Consumer Types (2022) 2030 climate & energy framework

Reference 2

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Observation c9299ce9-a12e-4a33-b9d3-1043f61be9dc · outbound

This paper cites Reliability improvements from the application of distribution automation technologies,.

Leveraging Hypernetworks and Learnable Kernels for Consumer Energy Forecasting Across Diverse Consumer Types Reliability improvements from the application of distribution automation technologies,

Reference 3

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This paper cites Application of decoupled ARMA model to modal identification of linear time- varying system based on the ICA and assumption of “short-time linearly varying.

Leveraging Hypernetworks and Learnable Kernels for Consumer Energy Forecasting Across Diverse Consumer Types Application of decoupled ARMA model to modal identification of linear time- varying system based on the ICA and assumption of “short-time linearly varying

Reference 4

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This paper cites A survey on deep learning methods for power load and renewable energy forecasting in smart microgrids,.

Leveraging Hypernetworks and Learnable Kernels for Consumer Energy Forecasting Across Diverse Consumer Types A survey on deep learning methods for power load and renewable energy forecasting in smart microgrids,

Reference 5

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This paper cites Transformer-based model for electrical load forecasting,.

Leveraging Hypernetworks and Learnable Kernels for Consumer Energy Forecasting Across Diverse Consumer Types Transformer-based model for electrical load forecasting,

Reference 6

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Observation 1e4adf7d-98f1-4836-a5e6-0100e2fb2857 · outbound

This paper cites Day-ahead building- level load forecasts using deep learning vs. traditional time-series tech- niques,.

Leveraging Hypernetworks and Learnable Kernels for Consumer Energy Forecasting Across Diverse Consumer Types Day-ahead building- level load forecasts using deep learning vs. traditional time-series tech- niques,

Reference 7

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Observation ec7527ed-fe40-486e-98a6-0aa30539e347 · outbound

This paper cites Long-term Forecasting with TiDE: Time-series Dense Encoder.

Leveraging Hypernetworks and Learnable Kernels for Consumer Energy Forecasting Across Diverse Consumer Types Long-term Forecasting with TiDE: Time-series Dense Encoder

Reference 8

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This paper cites A review of weight optimization techniques in recurrent neural networks,.

Leveraging Hypernetworks and Learnable Kernels for Consumer Energy Forecasting Across Diverse Consumer Types A review of weight optimization techniques in recurrent neural networks,

Reference 9

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Observation b1f4604c-1b3e-49ca-908f-4e7afdaa86d4 · outbound

This paper cites Peak reduction and long term load forecasting for large residential communities including smart homes with energy storage,.

Leveraging Hypernetworks and Learnable Kernels for Consumer Energy Forecasting Across Diverse Consumer Types Peak reduction and long term load forecasting for large residential communities including smart homes with energy storage,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:17:50.942541Z

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Observation dbb924e5-5436-4c44-8621-1dc007c92d3d · outbound

This paper cites Optimal real-time energy management in apartment building integrating microgrid with multizone hvac control,.

Leveraging Hypernetworks and Learnable Kernels for Consumer Energy Forecasting Across Diverse Consumer Types Optimal real-time energy management in apartment building integrating microgrid with multizone hvac control,

Reference 11

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Observation 0ce3befc-9e38-400f-8a31-1ebe4e04760a · outbound

This paper cites Short-term residential load forecasting based on LSTM recurrent neural network,.

Leveraging Hypernetworks and Learnable Kernels for Consumer Energy Forecasting Across Diverse Consumer Types Short-term residential load forecasting based on LSTM recurrent neural network,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:17:50.911813Z

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Observation d603c4c5-4d22-49e9-a908-9ebdcc549bb1 · outbound

This paper cites Deep- learning-based probabilistic forecasting of electric vehicle charging load with a novel queuing model,.

Leveraging Hypernetworks and Learnable Kernels for Consumer Energy Forecasting Across Diverse Consumer Types Deep- learning-based probabilistic forecasting of electric vehicle charging load with a novel queuing model,

Reference 13

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Observation 8657a3df-34bb-45b6-bafd-8dd028a2f080 · outbound

This paper cites Forecasting residential energy consumption using support vector regressions,.

Leveraging Hypernetworks and Learnable Kernels for Consumer Energy Forecasting Across Diverse Consumer Types Forecasting residential energy consumption using support vector regressions,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:17:50.881990Z

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Observation 320bb294-ba4b-4c9b-a8f5-6fa7ce4922a9 · outbound

This paper cites Regression model-based short-term load forecasting for uni- versity campus load,.

Leveraging Hypernetworks and Learnable Kernels for Consumer Energy Forecasting Across Diverse Consumer Types Regression model-based short-term load forecasting for uni- versity campus load,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:17:50.866070Z

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Observation 9a367145-1b82-4aa1-a873-fd63ee5b974b · outbound

This paper cites Light gradient boosting machine (lightgbm) to forecasting data and assisting the defrosting strategy design of refrigerators,.

Leveraging Hypernetworks and Learnable Kernels for Consumer Energy Forecasting Across Diverse Consumer Types Light gradient boosting machine (lightgbm) to forecasting data and assisting the defrosting strategy design of refrigerators,

Reference 16

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This paper cites N-beats neural network for mid-term electricity load forecasting,.

Leveraging Hypernetworks and Learnable Kernels for Consumer Energy Forecasting Across Diverse Consumer Types N-beats neural network for mid-term electricity load forecasting,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:17:50.834292Z

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Observation 308efeba-634b-41e2-9eff-116f2d44fc5e · outbound

This paper cites A new approach to seasonal energy consumption forecasting using temporal convolutional networks,.

Leveraging Hypernetworks and Learnable Kernels for Consumer Energy Forecasting Across Diverse Consumer Types A new approach to seasonal energy consumption forecasting using temporal convolutional networks,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:17:50.819641Z

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Observation 100c0dc3-8db3-4c49-9af9-a75732e832d9 · outbound

This paper cites A comparison between ARIMA, LSTM, and GRU for time series forecasting,.

Leveraging Hypernetworks and Learnable Kernels for Consumer Energy Forecasting Across Diverse Consumer Types A comparison between ARIMA, LSTM, and GRU for time series forecasting,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:17:50.804668Z

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Observation 678b206b-acef-451d-9ced-761556d289d9 · outbound

This paper cites Interval load forecasting for individual households in the presence of electric vehicle charging,.

Leveraging Hypernetworks and Learnable Kernels for Consumer Energy Forecasting Across Diverse Consumer Types Interval load forecasting for individual households in the presence of electric vehicle charging,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:17:50.790126Z

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Observation 4e6b5b3d-9783-4526-9de0-e9ef20058c42 · outbound

This paper cites Attention is all you need,.

Leveraging Hypernetworks and Learnable Kernels for Consumer Energy Forecasting Across Diverse Consumer Types Attention is all you need,

Reference 21

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Observation 73efe85e-0eeb-4be7-b7b5-09acd645371f · outbound

This paper cites Short-term electrical load forecasting using hybrid model of manta ray foraging optimization and support vector regression,.

Leveraging Hypernetworks and Learnable Kernels for Consumer Energy Forecasting Across Diverse Consumer Types Short-term electrical load forecasting using hybrid model of manta ray foraging optimization and support vector regression,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:17:50.766214Z

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Observation b6fa87eb-758f-4196-9837-7aa194d888d0 · outbound

This paper cites A novel hybrid model for building heat load forecasting based on multivariate empirical modal decomposition,.

Leveraging Hypernetworks and Learnable Kernels for Consumer Energy Forecasting Across Diverse Consumer Types A novel hybrid model for building heat load forecasting based on multivariate empirical modal decomposition,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:17:50.752401Z

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This paper cites AR-Net: A simple Auto-Regressive Neural Network for time-series.

Leveraging Hypernetworks and Learnable Kernels for Consumer Energy Forecasting Across Diverse Consumer Types AR-Net: A simple Auto-Regressive Neural Network for time-series

Reference 24

Resolution: verified exact; local_arxiv, observed 2026-08-08T20:17:50.466264Z

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Observation a24b3046-0389-4fe8-8079-ca201a0a5a85 · outbound

This paper cites A hybrid short- term load forecasting approach for individual residential customer,.

Leveraging Hypernetworks and Learnable Kernels for Consumer Energy Forecasting Across Diverse Consumer Types A hybrid short- term load forecasting approach for individual residential customer,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:17:50.737379Z

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Observation 08994b9b-03be-41ea-9580-8de6d85e2d08 · outbound

This paper cites Hy- permorph: Amortized hyperparameter learning for image registration,.

Leveraging Hypernetworks and Learnable Kernels for Consumer Energy Forecasting Across Diverse Consumer Types Hy- permorph: Amortized hyperparameter learning for image registration,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:17:50.723743Z

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This paper cites A ‘self-referential’weight matrix,.

Leveraging Hypernetworks and Learnable Kernels for Consumer Energy Forecasting Across Diverse Consumer Types A ‘self-referential’weight matrix,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:17:50.709864Z

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Observation 3d34cae4-f29f-4156-89cc-4f5e3f173202 · outbound

This paper cites Dhp: Differen- tiable meta pruning via hypernetworks,.

Leveraging Hypernetworks and Learnable Kernels for Consumer Energy Forecasting Across Diverse Consumer Types Dhp: Differen- tiable meta pruning via hypernetworks,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:17:50.695309Z

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Observation 1a136cfd-07a3-4743-8964-ab1b5778ccf3 · outbound

This paper cites Modular universal reparameteriza- tion: Deep multi-task learning across diverse domains,.

Leveraging Hypernetworks and Learnable Kernels for Consumer Energy Forecasting Across Diverse Consumer Types Modular universal reparameteriza- tion: Deep multi-task learning across diverse domains,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:17:50.681161Z

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This paper cites Hypernetwork functional image representation,.

Leveraging Hypernetworks and Learnable Kernels for Consumer Energy Forecasting Across Diverse Consumer Types Hypernetwork functional image representation,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:17:50.667196Z

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Observation 366dbdca-34b4-4a98-a88c-c00abd43a8dd · outbound

This paper cites Hypergan: A generative model for diverse, performant neural networks,.

Leveraging Hypernetworks and Learnable Kernels for Consumer Energy Forecasting Across Diverse Consumer Types Hypergan: A generative model for diverse, performant neural networks,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:17:50.651878Z

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Observation d4ce7a46-b2fc-4e0a-8807-344ea4bd194f · outbound

This paper cites HyperRS: Hypernetwork-based recommender system for the user cold-start problem,.

Leveraging Hypernetworks and Learnable Kernels for Consumer Energy Forecasting Across Diverse Consumer Types HyperRS: Hypernetwork-based recommender system for the user cold-start problem,

Reference 32

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Observation efc53710-193a-42f8-a980-02aac040f525 · outbound

This paper cites Differential privacy in hypernetworks for personalized federated learning,.

Leveraging Hypernetworks and Learnable Kernels for Consumer Energy Forecasting Across Diverse Consumer Types Differential privacy in hypernetworks for personalized federated learning,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:17:50.622492Z

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Observation 78c193a6-d6b7-4cd7-bc09-8b881512e733 · outbound

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Leveraging Hypernetworks and Learnable Kernels for Consumer Energy Forecasting Across Diverse Consumer Types SVM kernel based on particle swarm optimized vector and bayesian optimized SVM in atmospheric particulate matter forecasting,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:17:50.607667Z

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Observation 0c912c3f-1e43-4fbb-892a-312d3a590eea · outbound

This paper cites Searching for Activation Functions.

Leveraging Hypernetworks and Learnable Kernels for Consumer Energy Forecasting Across Diverse Consumer Types Searching for Activation Functions

Reference 35

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Observation fe2eaa5f-4dfd-4583-8449-5659605618c3 · outbound

This paper cites The building data genome project 2, energy meter data from the ASHRAE great energy predictor III competition,.

Leveraging Hypernetworks and Learnable Kernels for Consumer Energy Forecasting Across Diverse Consumer Types The building data genome project 2, energy meter data from the ASHRAE great energy predictor III competition,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:17:50.592550Z

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Observation 6ca56199-3328-4206-a0ff-87b8f49c0dcb · outbound

This paper cites Asynchronous adaptive federated learning for distributed load forecasting with smart meter data,.

Leveraging Hypernetworks and Learnable Kernels for Consumer Energy Forecasting Across Diverse Consumer Types Asynchronous adaptive federated learning for distributed load forecasting with smart meter data,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:17:50.576678Z

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Observation e6e06a05-6fb5-4a01-9067-683234900474 · outbound

This paper cites Transformer-based model for electrical load forecasting,.

Leveraging Hypernetworks and Learnable Kernels for Consumer Energy Forecasting Across Diverse Consumer Types Transformer-based model for electrical load forecasting,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:17:50.560392Z

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Observation addaa5a7-43f2-4a83-8983-8b9ead678d2b · outbound

This paper cites Effectiveness of learning rate in dementia severity prediction using VGG16,.

Leveraging Hypernetworks and Learnable Kernels for Consumer Energy Forecasting Across Diverse Consumer Types Effectiveness of learning rate in dementia severity prediction using VGG16,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:17:50.545119Z

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Observation d7b59a28-8e4d-4849-bf1e-dea606f2221a · outbound

This paper cites On weight initialization in deep neural networks.

Leveraging Hypernetworks and Learnable Kernels for Consumer Energy Forecasting Across Diverse Consumer Types On weight initialization in deep neural networks

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-08T20:17:50.379242Z

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This paper cites Multi-task short-term reactive and active load forecasting method based on attention-lstm model,.

Leveraging Hypernetworks and Learnable Kernels for Consumer Energy Forecasting Across Diverse Consumer Types Multi-task short-term reactive and active load forecasting method based on attention-lstm model,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:17:50.528784Z

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Observation 9a32ab2f-0c34-479a-a14c-c96096fbda68 · outbound

This paper cites Short term electricity load forecasting using hybrid prophet-lstm model optimized by bpnn,.

Leveraging Hypernetworks and Learnable Kernels for Consumer Energy Forecasting Across Diverse Consumer Types Short term electricity load forecasting using hybrid prophet-lstm model optimized by bpnn,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:17:50.513548Z

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Observation 02d4cb22-6fda-4dd0-b920-b234a5e56194 · outbound

This paper cites Methods of forecasting electric energy consumption: A literature review,.

Leveraging Hypernetworks and Learnable Kernels for Consumer Energy Forecasting Across Diverse Consumer Types Methods of forecasting electric energy consumption: A literature review,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:17:50.497377Z

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Observation e974209c-3013-4cde-90ec-9aeb1dfb07ad · outbound

This paper cites Available: https://www.energy.gov/sites/prod/files/2016/ 10/f33/Distribution Reliability Report - Final Dec 2012.pdf.

Leveraging Hypernetworks and Learnable Kernels for Consumer Energy Forecasting Across Diverse Consumer Types Available: https://www.energy.gov/sites/prod/files/2016/ 10/f33/Distribution Reliability Report - Final Dec 2012.pdf

Reference 2012

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:17:51.033805Z

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