by instadatahelp | Sep 6, 2023 | AI Blogs
Bayesian Spiked Laplacian Graphs Authors: Leo L Duan, George Michailidis, Mingzhou Ding; Volume 24(3):1−35, 2023. Abstract In the field of network analysis, it is common to encounter a collection of graphs that exhibit heterogeneity. For instance, there is an...
![A Token-Level Autoregressive Generative Model of Message Flow Using Deep State Space Network: Exploring Generative AI for End-to-End Limit Order Book Modelling (arXiv:2309.00638v1 [q-fin.TR])](https://instadatanews.com/wp-content/uploads/2023/08/arxiv-logo-fb-1080x675.png)
by instadatahelp | Sep 6, 2023 | AI Blogs
Developing a realistic generative model for order flow in financial markets is a complex problem with various potential applications for market participants. In this study, we propose an innovative autoregressive generative model that can produce tokenized limit order...
by instadatahelp | Sep 6, 2023 | AI Blogs
Combinatorial Optimization and Reasoning with Graph Neural Networks Quentin Cappart, Didier Chételat, Elias B. Khalil, Andrea Lodi, Christopher Morris, Petar Velickovic; 24(130):1−61, 2023. Abstract Combinatorial optimization, a well-established field in operations...
by instadatahelp | Sep 6, 2023 | AI Blogs
The content discusses the potential use of carbon fiber composite as a replacement for metal-based battery enclosures in electric vehicles (E.V.s). The advantages of carbon fiber, such as its strength-to-weight ratio and corrosion resistance, make it a suitable...
by instadatahelp | Sep 6, 2023 | AI Blogs
Cluster-Specific Predictions with Multi-Task Gaussian Processes Arthur Leroy, Pierre Latouche, Benjamin Guedj, Servane Gey; 24(5):1−49, 2023. Abstract This study introduces a model that utilizes Gaussian processes (GPs) to handle multitask learning, clustering, and...
by instadatahelp | Sep 6, 2023 | AI Blogs
This article examines the potential of deep reinforcement learning (DRL) methods in algorithmic commodities trading. The study presents a novel time-discretization scheme that adjusts to market volatility, improving the statistical properties of financial time series....
