A strategy for short-term load forecasting by support vector regression machines E Ceperic, V Ceperic, A Baric IEEE Transactions on Power Systems 28 (4), 4356-4364, 2013 | 499 | 2013 |
Integration of neural network-based symbolic regression in deep learning for scientific discovery S Kim, PY Lu, S Mukherjee, M Gilbert, L Jing, V Čeperić, M Soljačić IEEE transactions on neural networks and learning systems 32 (9), 4166-4177, 2020 | 167 | 2020 |
Heuristic recurrent algorithms for photonic Ising machines C Roques-Carmes, Y Shen, C Zanoci, M Prabhu, F Atieh, L Jing, ... Nature communications 11 (1), 249, 2020 | 111 | 2020 |
Accelerating recurrent Ising machines in photonic integrated circuits M Prabhu, C Roques-Carmes, Y Shen, N Harris, L Jing, J Carolan, ... Optica 7 (5), 551-558, 2020 | 100 | 2020 |
On-chip optical convolutional neural networks H Bagherian, S Skirlo, Y Shen, H Meng, V Ceperic, M Soljacic arXiv preprint arXiv:1808.03303, 2018 | 93 | 2018 |
Predictive and generative machine learning models for photonic crystals T Christensen, C Loh, S Picek, D Jakobović, L Jing, S Fisher, V Ceperic, ... Nanophotonics 9 (13), 4183-4192, 2020 | 91 | 2020 |
Short-term forecasting of natural gas prices using machine learning and feature selection algorithms E Čeperić, S Žiković, V Čeperić Energy 140, 893-900, 2017 | 86 | 2017 |
Modeling of analog circuits by using support vector regression machines V Ceperic, A Baric Proceedings of the 2004 11th IEEE International Conference on Electronics …, 2004 | 38 | 2004 |
A symbolic regression-based modelling strategy of AC/DC rectifiers for RFID applications V Ceperic, N Bako, A Baric Expert Systems with Applications 41 (16), 7061-7067, 2014 | 34 | 2014 |
Design and optimization of self-biased complementary folded cascode V Ceperic, Z Butkovic, A Baric MELECON 2006-2006 IEEE Mediterranean Electrotechnical Conference, 145-148, 2006 | 31 | 2006 |
Echo state networks for black-box modeling of integrated circuits M Magerl, V Ceperic, A Baric IEEE transactions on computer-aided design of integrated circuits and …, 2015 | 22 | 2015 |
Recurrent sparse support vector regression machines trained by active learning in the time-domain V Ceperic, G Gielen, A Baric Expert systems with applications 39 (12), 10933-10942, 2012 | 21 | 2012 |
Area-efficient differential Gaussian circuit for dedicated hardware implementations of Gaussian function based machine learning algorithms D Vrtaric, V Ceperic, A Baric Neurocomputing 118, 329-333, 2013 | 15 | 2013 |
Sparse multikernel support vector regression machines trained by active learning V Ceperic, G Gielen, A Baric Expert systems with applications 39 (12), 11029-11035, 2012 | 15 | 2012 |
Photonic recurrent Ising sampler C Roques-Carmes, Y Shen, C Zanoci, M Prabhu, F Atieh, L Jing, ... CLEO: QELS_Fundamental Science, FTu4C. 2, 2019 | 14 | 2019 |
Reducing complexity of echo state networks with sparse linear regression algorithms V Ceperic, A Baric 2014 UKSim-AMSS 16th International Conference on Computer Modelling and …, 2014 | 14 | 2014 |
Modelling of electromagnetic immunity of integrated circuits by artificial neural networks V Ceperic, A Baric 2009 20th International Zurich Symposium on Electromagnetic Compatibility …, 2009 | 13 | 2009 |
Sparse -tube support vector regression by active learning V Ceperic, G Gielen, A Baric Soft computing 18 (6), 1113-1126, 2014 | 12 | 2014 |
A recurrent ising machine in a photonic integrated circuit M Prabhu, C Roques-Carmes, Y Shen, N Harris, L Jing, J Carolan, ... arXiv preprint arXiv:1909.13877, 2019 | 9 | 2019 |
Black-box modelling of conducted electromagnetic immunity by support vector machines V Ceperic, G Gielen, A Baric International Symposium on Electromagnetic Compatibility-EMC EUROPE, 1-6, 2012 | 7 | 2012 |