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Found 8 papers, 1 papers with code
The Bid Picture: Auction-Inspired Multi-player Generative Adversarial Networks Training
This article proposes auction-inspired multi-player generative adversarial networks training, which mitigates the mode collapse problem of GANs.
TT-BLIP: Enhancing Fake News Detection Using BLIP and Tri-Transformer
This paper introduces an end-to-end model called TT-BLIP that applies the bootstrapping language-image pretraining for unified vision-language understanding and generation (BLIP) for three types of information: BERT and BLIP\textsubscript{Txt} for text, ResNet and BLIP\textsubscript{Img} for images, and bidirectional BLIP encoders for multimodal information.
Using a Deep Learning Model to Simulate Human Stock Trader's Methods of Chart Analysis
The backtest is done using the data from 2020 to 2022.
Cross-Modal Contrastive Representation Learning for Audio-to-Image Generation
Multiple modalities for certain information provide a variety of perspectives on that information, which can improve the understanding of the information.
Micro Batch Streaming: Allowing the Training of DNN Models to Use a large Batch Size in Memory Constrained Environments
This method helps deep learning models to train by providing a batch streaming method that splits a batch into a size that can fit in the remaining memory and streams them sequentially.
Introduction to Quantum Reinforcement Learning: Theory and PennyLane-based Implementation
The emergence of quantum computing enables for researchers to apply quantum circuit on many existing studies.
Contextual Skipgram: Training Word Representation Using Context Information
The skip-gram (SG) model learns word representation by predicting the words surrounding a center word from unstructured text data.
Privacy-Preserving Deep Learning Computation for Geo-Distributed Medical Big-Data Platforms
This paper proposes a distributed deep learning framework for privacy-preserving medical data training.
