Author of the publication

Sparse Recurrent Mixture Density Networks for Forecasting High Variability Time Series with Confidence Estimates.

, , and . ICANN (2), volume 11728 of Lecture Notes in Computer Science, page 422-433. Springer, (2019)

Please choose a person to relate this publication to

To differ between persons with the same name, the academic degree and the title of an important publication will be displayed. You can also use the button next to the name to display some publications already assigned to the person.

 

Other publications of authors with the same name

lEarn: A Reinforcement Learning Based Bidding Strategy for Generators in Single sided Energy Markets., , , , , , and . e-Energy, page 121-127. ACM, (2019)Bidding in Smart Grid PDAs: Theory, Analysis and Strategy (Extended Version)., , , , and . CoRR, (2019)Load Forecasting in Energy Markets: An Approach Using Sparse Neural Networks., and . e-Energy, page 403-405. ACM, (2019)Electricity Consumption Forecasting for Out-of-distribution Time-of-Use Tariffs., , , , , and . CoRR, (2022)VidyutVanika: A Reinforcement Learning Based Broker Agent for a Power Trading Competition., , , , and . AAAI, page 914-921. AAAI Press, (2019)Bidding Strategy for Two-Sided Electricity Markets: A Reinforcement Learning based Framework., , , , and . BuildSys@SenSys, page 110-119. ACM, (2020)Explicit solutions of discrete-time quadratic optimal hedging strategies for European contingent claims., and . CIFEr, page 449-456. IEEE, (2014)Bidding in Smart Grid PDAs: Theory, Analysis and Strategy., , , , and . AAAI, page 1974-1981. AAAI Press, (2020)Multi-unit Double Auctions: Equilibrium Analysis and Bidding Strategy using DDPG in Smart-grids., , , , and . AAMAS, page 1569-1571. International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS), (2022)Sparse Recurrent Mixture Density Networks for Forecasting High Variability Time Series with Confidence Estimates., , and . ICANN (2), volume 11728 of Lecture Notes in Computer Science, page 422-433. Springer, (2019)