Stefan Zohren

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 60

Top Topics

Maximum Entropy

Top Venues

IEEE Trans. Inf. Theory

Publications

Felix Drinkall, Janet B. Pierrehumbert, Stefan Zohren
Traditional Methods Outperform Generative LLMs at Forecasting Credit Ratings. CoRR (2024)
Sanjay Purushotham, Dongjin Song, Qingsong Wen, Jun Huan, Cong Shen, Stefan Zohren, Yuriy Nevmyvaka
The 10th Mining and Learning from Time Series Workshop: From Classical Methods to LLMs. KDD (2024)
Felix Drinkall, Eghbal Rahimikia, Janet B. Pierrehumbert, Stefan Zohren
Time Machine GPT. CoRR (2024)
Yoontae Hwang, Stefan Zohren, Yongjae Lee
Temporal Representation Learning for Stock Similarities and Its Applications in Investment Management. CoRR (2024)
Yuqi Nie, Yaxuan Kong, Xiaowen Dong, John M. Mulvey, H. Vincent Poor, Qingsong Wen, Stefan Zohren
A Survey of Large Language Models for Financial Applications: Progress, Prospects and Challenges. CoRR (2024)
Wee Ling Tan, Stephen J. Roberts, Stefan Zohren
Deep Learning for Options Trading: An End-To-End Approach. CoRR (2024)
Yichi Zhang, Mihai Cucuringu, Alexander Y. Shestopaloff, Stefan Zohren
Robust Detection of Lead-Lag Relationships in Lagged Multi-Factor Models. CoRR (2023)
Xingyue Pu, Stephen J. Roberts, Xiaowen Dong, Stefan Zohren
Network Momentum across Asset Classes. CoRR (2023)
Wee Ling Tan, Stephen J. Roberts, Stefan Zohren
Spatio-Temporal Momentum: Jointly Learning Time-Series and Cross-Sectional Strategies. CoRR (2023)
Sascha Yves Frey, Kang Li, Peer Nagy, Silvia Sapora, Christopher Lu, Stefan Zohren, Jakob N. Foerster, Anisoara Calinescu
JAX-LOB: A GPU-Accelerated limit order book simulator to unlock large scale reinforcement learning for trading. ICAIF (2023)
Samuel Kessler, Adam D. Cobb, Tim G. J. Rudner, Stefan Zohren, Stephen J. Roberts
On Sequential Bayesian Inference for Continual Learning. CoRR (2023)
Kieran Wood, Samuel Kessler, Stephen J. Roberts, Stefan Zohren
Few-Shot Learning Patterns in Financial Time-Series for Trend-Following Strategies. CoRR (2023)
Peer Nagy, Sascha Frey, Silvia Sapora, Kang Li, Anisoara Calinescu, Stefan Zohren, Jakob N. Foerster
Generative AI for End-to-End Limit Order Book Modelling: A Token-Level Autoregressive Generative Model of Message Flow Using a Deep State Space Network. CoRR (2023)
Xingyue Pu, Stefan Zohren, Stephen J. Roberts, Xiaowen Dong
Learning to Learn Financial Networks for Optimising Momentum Strategies. CoRR (2023)
Samuel Kessler, Adam D. Cobb, Tim G. J. Rudner, Stefan Zohren, Stephen J. Roberts
On Sequential Bayesian Inference for Continual Learning. Entropy 25 (6) (2023)
Peer Nagy, Jan-Peter Calliess, Stefan Zohren
Asynchronous Deep Double Duelling Q-Learning for Trading-Signal Execution in Limit Order Book Markets. CoRR (2023)
Yichi Zhang, Mihai Cucuringu, Alexander Y. Shestopaloff, Stefan Zohren
Dynamic Time Warping for Lead-Lag Relationship Detection in Lagged Multi-Factor Models. ICAIF (2023)
Xinpeng Hong, Changgang Zheng, Stefan Zohren, Noa Zilberman
LOBIN: In-Network Machine Learning for Limit Order Books. HPSR (2023)
Sascha Frey, Kang Li, Peer Nagy, Silvia Sapora, Chris Lu, Stefan Zohren, Jakob N. Foerster, Anisoara Calinescu
JAX-LOB: A GPU-Accelerated limit order book simulator to unlock large scale reinforcement learning for trading. CoRR (2023)
Peer Nagy, Jan-Peter Calliess, Stefan Zohren
Asynchronous Deep Double Dueling Q-learning for trading-signal execution in limit order book markets. Frontiers Artif. Intell. 6 (2023)
Peer Nagy, Sascha Frey, Silvia Sapora, Kang Li, Anisoara Calinescu, Stefan Zohren, Jakob N. Foerster
Generative AI for End-to-End Limit Order Book Modelling: A Token-Level Autoregressive Generative Model of Message Flow Using a Deep State Space Network. ICAIF (2023)
Felix Drinkall, Stefan Zohren, Janet B. Pierrehumbert
Forecasting COVID-19 Caseloads Using Unsupervised Embedding Clusters of Social Media Posts. CoRR (2022)
Daniel Poh, Stephen J. Roberts, Stefan Zohren
Transfer Ranking in Finance: Applications to Cross-Sectional Momentum with Data Scarcity. CoRR (2022)
Dragos Gorduza, Xiaowen Dong, Stefan Zohren
Understanding stock market instability via graph auto-encoders. CoRR (2022)
Diego Granziol, Binxin Ru, Xiaowen Dong, Stefan Zohren, Michael A. Osborne, Stephen J. Roberts
Maximum Entropy Approach to Massive Graph Spectrum Learning with Applications. Algorithms 15 (6) (2022)
Diego Granziol, Stefan Zohren, Stephen Roberts
Learning Rates as a Function of Batch Size: A Random Matrix Theory Approach to Neural Network Training. J. Mach. Learn. Res. 23 (2022)
Samuel Kessler, Jack Parker-Holder, Philip J. Ball, Stefan Zohren, Stephen J. Roberts
Same State, Different Task: Continual Reinforcement Learning without Interference. AAAI (2022)
Felix Drinkall, Stefan Zohren, Janet B. Pierrehumbert
Forecasting COVID-19 Caseloads Using Unsupervised Embedding Clusters of Social Media Posts. NAACL-HLT (2022)
Xinpeng Hong, Changgang Zheng, Stefan Zohren, Noa Zilberman
Linnet: limit order books within switches. SIGCOMM Posters and Demos (2022)
Fernando Moreno-Pino, Stefan Zohren
DeepVol: Volatility Forecasting from High-Frequency Data with Dilated Causal Convolutions. CoRR (2022)
Kieran Wood, Sven Giegerich, Stephen J. Roberts, Stefan Zohren
Trading with the Momentum Transformer: An Intelligent and Interpretable Architecture. CoRR (2021)
Samuel Kessler, Jack Parker-Holder, Philip J. Ball, Stefan Zohren, Stephen J. Roberts
Same State, Different Task: Continual Reinforcement Learning without Interference. CoRR (2021)
Samuel Kessler, Vu Nguyen, Stefan Zohren, Stephen J. Roberts
Hierarchical Indian buffet neural networks for Bayesian continual learning. UAI (2021)
Daniel Poh, Bryan Lim, Stefan Zohren, Stephen J. Roberts
Enhancing Cross-Sectional Currency Strategies by Ranking Refinement with Transformer-based Architectures. CoRR (2021)
Peter Belcak, Jan-Peter Calliess, Stefan Zohren
Fast Agent-Based Simulation Framework with Applications to Reinforcement Learning and the Study of Trading Latency Effects. MABS (2021)
Zihao Zhang, Stefan Zohren
Multi-Horizon Forecasting for Limit Order Books: Novel Deep Learning Approaches and Hardware Acceleration using Intelligent Processing Units. CoRR (2021)
Zihao Zhang, Bryan Lim, Stefan Zohren
Deep Learning for Market by Order Data. CoRR (2021)
Kieran Wood, Stephen J. Roberts, Stefan Zohren
Slow Momentum with Fast Reversion: A Trading Strategy Using Deep Learning and Changepoint Detection. CoRR (2021)
Eghbal Rahimikia, Stefan Zohren, Ser-Huang Poon
Realised Volatility Forecasting: Machine Learning via Financial Word Embedding. CoRR (2021)
Bryan Lim, Stefan Zohren, Stephen Roberts
Detecting Changes in Asset Co-Movement Using the Autoencoder Reconstruction Ratio. CoRR (2020)
Xingchen Wan, Jie Yang, Slavi Marinov, Jan-Peter Calliess, Stefan Zohren, Xiaowen Dong
Sentiment Diffusion in Financial News Networks and Associated Market Movements. CoRR (2020)
Vincent W. C. Tan, Stefan Zohren
Large Non-Stationary Noisy Covariance Matrices: A Cross-Validation Approach. CoRR (2020)
Bryan Lim, Stefan Zohren, Stephen Roberts
Recurrent Neural Filters: Learning Independent Bayesian Filtering Steps for Time Series Prediction. IJCNN (2020)
Peter Belcak, Jan-Peter Calliess, Stefan Zohren
Fast Agent-Based Simulation Framework of Limit Order Books with Applications to Pro-Rata Markets and the Study of Latency Effects. CoRR (2020)
Joschka Roffe, Stefan Zohren, Dominic Horsman, Nicholas Chancellor
Quantum Codes From Classical Graphical Models. IEEE Trans. Inf. Theory 66 (1) (2020)
Zihao Zhang, Stefan Zohren, Stephen Roberts
Deep Learning for Portfolio Optimisation. CoRR (2020)
Daniel Poh, Bryan Lim, Stefan Zohren, Stephen J. Roberts
Building Cross-Sectional Systematic Strategies By Learning to Rank. CoRR (2020)
Bryan Lim, Stefan Zohren
Time Series Forecasting With Deep Learning: A Survey. CoRR (2020)
Zihao Zhang, Stefan Zohren, Stephen J. Roberts
Deep Reinforcement Learning for Trading. CoRR (2019)
Diego Granziol, Robin Ru, Stefan Zohren, Xiaowen Dong, Michael A. Osborne, Stephen J. Roberts
A Maximum Entropy approach to Massive Graph Spectra. CoRR (2019)
Bryan Lim, Stefan Zohren, Stephen J. Roberts
Population-based Global Optimisation Methods for Learning Long-term Dependencies with RNNs. CoRR (2019)
Bryan Lim, Stefan Zohren, Stephen J. Roberts
Recurrent Neural Filters: Learning Independent Bayesian Filtering Steps for Time Series Prediction. CoRR (2019)
Diego Granziol, Bin Xin Ru, Stefan Zohren, Xiaowen Dong, Michael A. Osborne, Stephen J. Roberts
MEMe: An Accurate Maximum Entropy Method for Efficient Approximations in Large-Scale Machine Learning. Entropy 21 (6) (2019)
Samuel Kessler, Vu Nguyen, Stefan Zohren, Stephen Roberts
Indian Buffet Neural Networks for Continual Learning. CoRR (2019)
Zihao Zhang, Stefan Zohren, Stephen J. Roberts
DeepLOB: Deep Convolutional Neural Networks for Limit Order Books. IEEE Trans. Signal Process. 67 (11) (2019)
Bryan Lim, Stefan Zohren, Stephen J. Roberts
Enhancing Time Series Momentum Strategies Using Deep Neural Networks. CoRR (2019)
Diego Granziol, Bin Xin Ru, Stefan Zohren, Xiaowen Dong, Michael A. Osborne, Stephen J. Roberts
MEMe: An Accurate Maximum Entropy Method for Efficient Approximations in Large-Scale Machine Learning. CoRR (2019)
Mariano Chouza, Stephen J. Roberts, Stefan Zohren
Gradient descent in Gaussian random fields as a toy model for high-dimensional optimisation in deep learning. CoRR (2018)
Diego Granziol, Bin Xin Ru, Stefan Zohren, Xiaowen Dong, Michael A. Osborne, Stephen J. Roberts
Entropic Spectral Learning in Large Scale Networks. CoRR (2018)
Arnold Salas, Stefan Zohren, Stephen J. Roberts
Practical Bayesian Learning of Neural Networks via Adaptive Subgradient Methods. CoRR (2018)