| Forecasting stock prices from the limit order book using convolutional neural networks A Tsantekidis, N Passalis, A Tefas, J Kanniainen, M Gabbouj, A Iosifidis 2017 IEEE 19th conference on business informatics (CBI) 1, 7-12, 2017 | 456 | 2017 |
| Using deep learning to detect price change indications in financial markets A Tsantekidis, N Passalis, A Tefas, J Kanniainen, M Gabbouj, A Iosifidis 2017 25th European signal processing conference (EUSIPCO), 2511-2515, 2017 | 192 | 2017 |
| Using deep learning for price prediction by exploiting stationary limit order book features A Tsantekidis, N Passalis, A Tefas, J Kanniainen, M Gabbouj, A Iosifidis Applied Soft Computing 93, 106401, 2020 | 114 | 2020 |
| Machine learning for forecasting mid-price movements using limit order book data P Nousi, A Tsantekidis, N Passalis, A Ntakaris, J Kanniainen, A Tefas, ... Ieee Access 7, 64722-64736, 2019 | 71 | 2019 |
| Price trailing for financial trading using deep reinforcement learning A Tsantekidis, N Passalis, AS Toufa, K Saitas-Zarkias, S Chairistanidis, ... IEEE Transactions on neural networks and learning systems 32 (7), 2837-2846, 2020 | 67 | 2020 |
| Deep reinforcement learning for financial trading using price trailing KS Zarkias, N Passalis, A Tsantekidis, A Tefas ICASSP 2019-2019 IEEE international conference on acoustics, speech and …, 2019 | 63 | 2019 |
| Time-series classification using neural bag-of-features N Passalis, A Tsantekidis, A Tefas, J Kanniainen, M Gabbouj, A Iosifidis 2017 25th European Signal Processing Conference (EUSIPCO), 301-305, 2017 | 53 | 2017 |
| Diversity-driven knowledge distillation for financial trading using deep reinforcement learning A Tsantekidis, N Passalis, A Tefas Neural Networks 140, 193-202, 2021 | 43 | 2021 |
| Recurrent neural networks A Tsantekidis, N Passalis, A Tefas Deep learning for robot perception and cognition, 101-115, 2022 | 37 | 2022 |
| Multisource financial sentiment analysis for detecting Bitcoin price change indications using deep learning N Passalis, L Avramelou, S Seficha, A Tsantekidis, S Doropoulos, ... Neural Computing and Applications 34 (22), 19441-19452, 2022 | 20 | 2022 |
| Transferring trading strategy knowledge to deep learning models A Tsantekidis, A Tefas Knowledge and Information Systems 63 (1), 87-104, 2021 | 11 | 2021 |
| Deep reinforcement learning A Tsantekidis, N Passalis, A Tefas Deep Learning for Robot Perception and Cognition, 117-129, 2022 | 9 | 2022 |
| Improving deep reinforcement learning for financial trading using neural network distillation A Tsantekidis, N Passalis, A Tefas 2020 IEEE 30th International Workshop on Machine Learning for Signal …, 2020 | 9 | 2020 |
| Learning sentiment-aware trading strategies for bitcoin leveraging deep learning-based financial news analysis N Passalis, S Seficha, A Tsantekidis, A Tefas Artificial Intelligence Applications and Innovations: 17th IFIP WG 12.5 …, 2021 | 7 | 2021 |
| Modeling limit order trading with a continuous action policy for deep reinforcement learning A Tsantekidis, N Passalis, A Tefas Neural Networks 165, 506-515, 2023 | 5 | 2023 |
| Improving Deep Reinforcement Learning for Financial Trading Using Deep Adaptive Group-Based Normalization A Nalmpantis, N Passalis, A Tsantekidis, A Tefas 2021 IEEE 31st International Workshop on Machine Learning for Signal …, 2021 | 4 | 2021 |
| Online Knowledge Distillation for Financial Timeseries Forecasting P Floratos, A Tsantekidis, N Passalis, A Tefas 2022 International Conference on INnovations in Intelligent SysTems and …, 2022 | 3 | 2022 |
| Deep adaptive group-based input normalization for financial trading A Nalmpantis, N Passalis, A Tsantekidis, A Tefas Pattern Recognition Letters 152, 413-419, 2021 | 3 | 2021 |
| Sentiment-Aware Distillation for Bitcoin Trend Forecasting Under Partial Observability G Panagiotatos, N Passalis, A Tsantekidis, A Tefas ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and …, 2022 | 2 | 2022 |
| Leveraging Deep Learning and Online Source Sentiment for Financial Portfolio Management P Nousi, L Avramelou, G Rodinos, M Tzelepi, T Manousis, K Tsampazis, ... arXiv preprint arXiv:2309.16679, 2023 | 1 | 2023 |
