Juho Kanniainen

64 papers B 1Misc 2Journal 52Unranked 9

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Corrigendum to "Augmented bilinear network for incremental multi-stock time-series classification" [Pattern Recognit. 141 (2023) 109604]. Pattern Recognit. Mostafa Shabani, Dat Thanh Tran, Juho Kanniainen, Alexandros Iosifidis
2026	J	`jnl`	Optimizing the Output of Long Short-Term Memory Cell for High-Frequency Forecasting in Financial Markets. IEEE Trans. Neural Networks Learn. Syst. Adamantios Ntakaris, Moncef Gabbouj, Juho Kanniainen
2026	J	`jnl`	Topological clustering of agents in information contagions: Application to financial markets. Expert Syst. Appl. Anubha Goel, Henri Hansen, Juho Kanniainen
2025	J	`jnl`	Forecasting Mortality Associated Emergency Department Crowding with LightGBM and Time Series Data. J. Medical Syst. Jalmari Nevanlinna, Anna Eidstø, Jari Ylä-Mattila, Teemu Koivistoinen, Niku Oksala, Juho Kanniainen, Ari Palomäki, Antti Roine
2025	J	`jnl`	LOBERT: Generative AI Foundation Model for Limit Order Book Messages. CoRR Eljas Linna, Kestutis Baltakys, Alexandros Iosifidis, Juho Kanniainen
2025	J	`jnl`	Learning hidden cascades via classification. CoRR Derrick Gilchrist Edward Manoharan, Anubha Goel, Alexandros Iosifidis, Henri Hansen, Juho Kanniainen
2025	J	`jnl`	Variational Graph Convolutional Neural Networks. CoRR Illia Oleksiienko, Juho Kanniainen, Alexandros Iosifidis
2024	J	`jnl`	Detachment Problem - Application in Prevention of Information Leakage in Stock Markets. CoRR Henri Hansen, Juho Kanniainen
2024	J	`jnl`	Forecasting mortality associated emergency department crowding. CoRR Jalmari Nevanlinna, Anna Eidstø, Jari Ylä-Mattila, Teemu Koivistoinen, Niku Oksala, Juho Kanniainen, Ari Palomäki, Antti Roine
2024	J	`jnl`	Time-Series Foundation Model for Value-at-Risk. CoRR Anubha Goel, Puneet Pasricha, Juho Kanniainen
2024	J	`jnl`	Valuation of option price in commodity markets described by a Markov-switching model: A case study of WTI crude oil market. Math. Comput. Simul. Farshid Mehrdoust, Idin Noorani, Juho Kanniainen
2023	J	`jnl`	Augmented bilinear network for incremental multi-stock time-series classification. Pattern Recognit. Mostafa Shabani, Dat Thanh Tran, Juho Kanniainen, Alexandros Iosifidis
2023	—	`conf`	Credit Card Fraud Detection with Subspace Learning-based One-Class Classification. SSCI Zaffar Zaffar, Fahad Sohrab, Juho Kanniainen, Moncef Gabbouj
2023	J	`jnl`	Credit Card Fraud Detection with Subspace Learning-based One-Class Classification. CoRR Zaffar Zaffar, Fahad Sohrab, Juho Kanniainen, Moncef Gabbouj
2023	—	`conf`	Cryptocurrency Portfolio Optimization by Neural Networks. SSCI Quoc Minh Nguyen, Dat Thanh Tran, Juho Kanniainen, Alexandros Iosifidis, Moncef Gabbouj
2023	J	`jnl`	Cryptocurrency Portfolio Optimization by Neural Networks. CoRR Quoc Minh Nguyen, Dat Thanh Tran, Juho Kanniainen, Alexandros Iosifidis, Moncef Gabbouj
2023	J	`jnl`	Early Warning Software for Emergency Department Crowding. CoRR Jalmari Tuominen, Teemu Koivistoinen, Juho Kanniainen, Niku Oksala, Ari Palomäki, Antti Roine
2023	J	`jnl`	Early Warning Software for Emergency Department Crowding. J. Medical Syst. Jalmari Tuominen, Teemu Koivistoinen, Juho Kanniainen, Niku Oksala, Ari Palomäki, Antti Roine
2023	J	`jnl`	Forecasting Emergency Department Crowding with Advanced Machine Learning Models and Multivariable Input. CoRR Jalmari Tuominen, Eetu Pulkkinen, Jaakko Peltonen, Juho Kanniainen, Niku Oksala, Ari Palomäki, Antti Roine
2023	J	`jnl`	Optimum Output Long Short-Term Memory Cell for High-Frequency Trading Forecasting. CoRR Adamantios Ntakaris, Moncef Gabbouj, Juho Kanniainen
2023	J	`jnl`	Predicting the state of synchronization of financial time series using cross recurrence plots. Neural Comput. Appl. Mostafa Shabani, Martin Magris, George Tzagkarakis, Juho Kanniainen, Alexandros Iosifidis
2023	J	`jnl`	Predicting the trading behavior of socially connected investors: Graph neural network approach with implications to market surveillance. Expert Syst. Appl. Kestutis Baltakys, Margarita Baltakiene, Negar Heidari, Alexandros Iosifidis, Juho Kanniainen
2023	J	`jnl`	Sparse Index Tracking via Topological Learning. CoRR Anubha Goel, Puneet Pasricha, Juho Kanniainen
2022	J	`jnl`	Augmented Bilinear Network for Incremental Multi-Stock Time-Series Classification. CoRR Mostafa Shabani, Dat Thanh Tran, Juho Kanniainen, Alexandros Iosifidis
2022	J	`jnl`	How informative is the Order Book Beyond the Best Levels? Machine Learning Perspective. CoRR Dat Thanh Tran, Juho Kanniainen, Alexandros Iosifidis
2022	—	`conf`	Multi-head Temporal Attention-Augmented Bilinear Network for Financial time series prediction. EUSIPCO Mostafa Shabani, Dat Thanh Tran, Martin Magris, Juho Kanniainen, Alexandros Iosifidis
2022	J	`jnl`	Multi-head Temporal Attention-Augmented Bilinear Network for Financial time series prediction. CoRR Mostafa Shabani, Dat Thanh Tran, Martin Magris, Juho Kanniainen, Alexandros Iosifidis
2022	J	`jnl`	Trade synchronization and social ties in stock markets. EPJ Data Sci. Margarita Baltakiene, Kestutis Baltakys, Juho Kanniainen
2021	J	`jnl`	Bilinear Input Normalization for Neural Networks in Financial Forecasting. CoRR Dat Thanh Tran, Juho Kanniainen, Moncef Gabbouj, Alexandros Iosifidis
2021	J	`jnl`	Forecasting Financial Time Series Using Robust Deep Adaptive Input Normalization. J. Signal Process. Syst. Nikolaos Passalis, Juho Kanniainen, Moncef Gabbouj, Alexandros Iosifidis, Anastasios Tefas
2021	J	`jnl`	Structure of Investor Networks and Financial Crises. Entropy Kestutis Baltakys, Hung Le Viet, Juho Kanniainen
2020	Misc	`conf`	Adaptive Normalization for Forecasting Limit Order Book Data Using Convolutional Neural Networks. ICASSP Nikolaos Passalis, Anastasios Tefas, Juho Kanniainen, Moncef Gabbouj, Alexandros Iosifidis
2020	B	`conf`	Data Normalization for Bilinear Structures in High-Frequency Financial Time-series. ICPR Dat Thanh Tran, Juho Kanniainen, Moncef Gabbouj, Alexandros Iosifidis
2020	J	`jnl`	Data Normalization for Bilinear Structures in High-Frequency Financial Time-series. CoRR Dat Thanh Tran, Juho Kanniainen, Moncef Gabbouj, Alexandros Iosifidis
2020	J	`jnl`	Deep Adaptive Input Normalization for Time Series Forecasting. IEEE Trans. Neural Networks Learn. Syst. Nikolaos Passalis, Anastasios Tefas, Juho Kanniainen, Moncef Gabbouj, Alexandros Iosifidis
2020	J	`jnl`	Temporal Bag-of-Features Learning for Predicting Mid Price Movements Using High Frequency Limit Order Book Data. IEEE Trans. Emerg. Top. Comput. Intell. Nikolaos Passalis, Anastasios Tefas, Juho Kanniainen, Moncef Gabbouj, Alexandros Iosifidis
2020	J	`jnl`	Temporal logistic neural Bag-of-Features for financial time series forecasting leveraging limit order book data. Pattern Recognit. Lett. Nikolaos Passalis, Anastasios Tefas, Juho Kanniainen, Moncef Gabbouj, Alexandros Iosifidis
2020	J	`jnl`	Using Deep Learning for price prediction by exploiting stationary limit order book features. Appl. Soft Comput. Avraam Tsantekidis, Nikolaos Passalis, Anastasios Tefas, Juho Kanniainen, Moncef Gabbouj, Alexandros Iosifidis
2019	J	`jnl`	Data-driven Neural Architecture Learning For Financial Time-series Forecasting. CoRR Dat Thanh Tran, Juho Kanniainen, Moncef Gabbouj, Alexandros Iosifidis
2019	J	`jnl`	Deep Adaptive Input Normalization for Price Forecasting using Limit Order Book Data. CoRR Nikolaos Passalis, Anastasios Tefas, Juho Kanniainen, Moncef Gabbouj, Alexandros Iosifidis
2019	Misc	`conf`	Deep Temporal Logistic Bag-of-features for Forecasting High Frequency Limit Order Book Time Series. ICASSP Nikolaos Passalis, Anastasios Tefas, Juho Kanniainen, Moncef Gabbouj, Alexandros Iosifidis
2019	J	`jnl`	Feature Engineering for Mid-Price Prediction With Deep Learning. IEEE Access Adamantios Ntakaris, Giorgio Mirone, Juho Kanniainen, Moncef Gabbouj, Alexandros Iosifidis
2019	J	`jnl`	Feature Engineering for Mid-Price Prediction with Deep Learning. CoRR Adamantios Ntakaris, Giorgio Mirone, Juho Kanniainen, Moncef Gabbouj, Alexandros Iosifidis
2019	J	`jnl`	Machine Learning for Forecasting Mid-Price Movements Using Limit Order Book Data. IEEE Access Paraskevi Nousi, Avraam Tsantekidis, Nikolaos Passalis, Adamantios Ntakaris, Juho Kanniainen, Anastasios Tefas, Moncef Gabbouj, Alexandros Iosifidis
2019	J	`jnl`	Mid-price Prediction Based on Machine Learning Methods with Technical and Quantitative Indicators. CoRR Adamantios Ntakaris, Juho Kanniainen, Moncef Gabbouj, Alexandros Iosifidis
2019	J	`jnl`	Temporal Attention-Augmented Bilinear Network for Financial Time-Series Data Analysis. IEEE Trans. Neural Networks Learn. Syst. Dat Thanh Tran, Alexandros Iosifidis, Juho Kanniainen, Moncef Gabbouj
2019	J	`jnl`	Temporal Logistic Neural Bag-of-Features for Financial Time series Forecasting leveraging Limit Order Book Data. CoRR Nikolaos Passalis, Anastasios Tefas, Juho Kanniainen, Moncef Gabbouj, Alexandros Iosifidis
2018	J	`jnl`	Machine Learning for Forecasting Mid Price Movement using Limit Order Book Data. CoRR Paraskevi Nousi, Avraam Tsantekidis, Nikolaos Passalis, Adamantios Ntakaris, Juho Kanniainen, Anastasios Tefas, Moncef Gabbouj, Alexandros Iosifidis
2018	J	`jnl`	Using Deep Learning for price prediction by exploiting stationary limit order book features. CoRR Avraam Tsantekidis, Nikolaos Passalis, Anastasios Tefas, Juho Kanniainen, Moncef Gabbouj, Alexandros Iosifidis
2017	J	`jnl`	Benchmark Dataset for Mid-Price Prediction of Limit Order Book data. CoRR Adamantios Ntakaris, Martin Magris, Juho Kanniainen, Moncef Gabbouj, Alexandros Iosifidis
2017	—	`conf`	Forecasting Stock Prices from the Limit Order Book Using Convolutional Neural Networks. CBI (1) Avraam Tsantekidis, Nikolaos Passalis, Anastasios Tefas, Juho Kanniainen, Moncef Gabbouj, Alexandros Iosifidis
2017	—	`conf`	Long-range auto-correlations in limit order book markets: Inter-and cross-event analysis. SSCI Martin Magris, Jiyeong Kim, Esa Räsänen, Juho Kanniainen
2017	J	`jnl`	Temporal Attention augmented Bilinear Network for Financial Time-Series Data Analysis. CoRR Dat Thanh Tran, Alexandros Iosifidis, Juho Kanniainen, Moncef Gabbouj
2017	J	`jnl`	Tensor Representation in High-Frequency Financial Data for Price Change Prediction. CoRR Dat Thanh Tran, Martin Magris, Juho Kanniainen, Moncef Gabbouj, Alexandros Iosifidis
2017	—	`conf`	Tensor representation in high-frequency financial data for price change prediction. SSCI Dat Thanh Tran, Martin Magris, Juho Kanniainen, Moncef Gabbouj, Alexandros Iosifidis
2017	—	`conf`	Time-series classification using neural Bag-of-Features. EUSIPCO Nikolaos Passalis, Avraam Tsantekidis, Anastasios Tefas, Juho Kanniainen, Moncef Gabbouj, Alexandros Iosifidis
2017	—	`conf`	Using deep learning to detect price change indications in financial markets. EUSIPCO Avraam Tsantekidis, Nikolaos Passalis, Anastasios Tefas, Juho Kanniainen, Moncef Gabbouj, Alexandros Iosifidis
2015	J	`jnl`	A fast universal self-tuned sampler within Gibbs sampling. Digit. Signal Process. Luca Martino, H. Yang, David Luengo, Juho Kanniainen, Jukka Corander
2013	J	`jnl`	Calibration of GARCH models using concurrent accelerated random search. Appl. Math. Comput. Juliane Müller, Juho Kanniainen, Robert Piché
2011	J	`jnl`	Forecasting the Diffusion of Innovation: A Stochastic Bass Model With Log-Normal and Mean-Reverting Error Process. IEEE Trans. Engineering Management Juho Kanniainen, Saku J. Mäkinen, Robert Piché, Alok Chakrabarti
2011	J	`jnl`	Option pricing under joint dynamics of interest rates, dividends, and stock prices. Oper. Res. Lett. Juho Kanniainen
2009	J	`jnl`	Can properly discounted projects follow geometric Brownian motion? Math. Methods Oper. Res. Juho Kanniainen
2009	J	`jnl`	Matrix-based numerical modelling of financial differential equations. Int. J. Math. Model. Numer. Optimisation Robert Piché, Juho Kanniainen
2007	—	`conf`	Solving financial differential equations using differentiation matrices. World Congress on Engineering Robert Piché, Juho Kanniainen