Time-series classification using neural Bag-of-Features. - Nikolaos Passalis; Avraam Tsantekidis; Anastasios Tefas; Juho Kanniainen; Moncef Gabbouj; Alexandros Iosifidis (EUSIPCO, 2017)

Using deep learning to detect price change indications in financial markets. - Avraam Tsantekidis; Nikolaos Passalis; Anastasios Tefas; Juho Kanniainen; Moncef Gabbouj; Alexandros Iosifidis (EUSIPCO, 2017)

Forecasting Stock Prices from the Limit Order Book Using Convolutional Neural Networks. - Avraam Tsantekidis; Nikolaos Passalis; Anastasios Tefas; Juho Kanniainen; Moncef Gabbouj; Alexandros Iosifidis (CBI (1), 2017)

Machine Learning for Forecasting Mid Price Movement using Limit Order Book Data. - Paraskevi Nousi; Avraam Tsantekidis; Nikolaos Passalis; Adamantios Ntakaris; Juho Kanniainen; Anastasios Tefas; Moncef Gabbouj; Alexandros Iosifidis (CoRR, 2018)

Deep Reinforcement Learning for Financial Trading Using Price Trailing. - Konstantinos Saitas Zarkias; Nikolaos Passalis; Avraam Tsantekidis; Anastasios Tefas (ICASSP, 2019)

Machine Learning for Forecasting Mid-Price Movements Using Limit Order Book Data. - Paraskevi Nousi; Avraam Tsantekidis; Nikolaos Passalis; Adamantios Ntakaris; Juho Kanniainen; Anastasios Tefas; Moncef Gabbouj; Alexandros Iosifidis (IEEE Access, 2019)

Improving Deep Reinforcement Learning for Financial Trading Using Neural Network Distillation. - Avraam Tsantekidis; Nikolaos Passalis; Anastasios Tefas (MLSP, 2020)

Using Deep Learning for price prediction by exploiting stationary limit order book features. - Avraam Tsantekidis; Nikolaos Passalis; Anastasios Tefas; Juho Kanniainen; Moncef Gabbouj; Alexandros Iosifidis (Appl. Soft Comput., 2020)

Learning Sentiment-Aware Trading Strategies for Bitcoin Leveraging Deep Learning-Based Financial News Analysis. - Nikolaos Passalis; Solon Seficha; Avraam Tsantekidis; Anastasios Tefas (AIAI, 2021)

Improving Deep Reinforcement Learning for Financial Trading Using Deep Adaptive Group-Based Normalization. - Angelos Nalmpantis; Nikolaos Passalis; Avraam Tsantekidis; Anastasios Tefas (MLSP, 2021)

Transferring trading strategy knowledge to deep learning models. - Avraam Tsantekidis; Anastasios Tefas (Knowl. Inf. Syst., 2021)

Diversity-driven knowledge distillation for financial trading using Deep Reinforcement Learning. - Avraam Tsantekidis; Nikolaos Passalis; Anastasios Tefas (Neural Networks, 2021)

Deep adaptive group-based input normalization for financial trading. - Angelos Nalmpantis; Nikolaos Passalis; Avraam Tsantekidis; Anastasios Tefas (Pattern Recognit. Lett., 2021)

Price Trailing for Financial Trading Using Deep Reinforcement Learning. - Avraam Tsantekidis; Nikolaos Passalis; Anastasia-Sotiria Toufa; Konstantinos Saitas Zarkias; Stergios Chairistanidis; Anastasios Tefas (IEEE Trans. Neural Networks Learn. Syst., 2021)

Deep learning techniques for financial data - Avraam Tsantekidis (2021)

Sentiment-Aware Distillation for Bitcoin Trend Forecasting Under Partial Observability. - Georgios Panagiotatos; Nikolaos Passalis; Avraam Tsantekidis; Anastasios Tefas (ICASSP, 2022)

Online Knowledge Distillation for Financial Timeseries Forecasting. - Pavlos Floratos; Avraam Tsantekidis; Nikolaos Passalis; Anastasios Tefas (INISTA, 2022)

Multisource financial sentiment analysis for detecting Bitcoin price change indications using deep learning. - Nikolaos Passalis; Loukia Avramelou; Solon Seficha; Avraam Tsantekidis; Stavros Doropoulos; Giorgos Makris; Anastasios Tefas (Neural Comput. Appl., 2022)

Leveraging Deep Learning and Online Source Sentiment for Financial Portfolio Management. - Paraskevi Nousi; Loukia Avramelou; Georgios Rodinos; Maria Tzelepi; Theodoros Manousis; Konstantinos Tsampazis; Kyriakos Stefanidis; Dimitris Spanos; Emmanouil Kirtas; Pavlos Tosidis; Avraam Tsantekidis; Nikolaos Passalis; et al. (CoRR, 2023)

Modeling limit order trading with a continuous action policy for deep reinforcement learning. - Avraam Tsantekidis; Nikolaos Passalis; Anastasios Tefas (Neural Networks, 2023)