Summary of Efficient User History Modeling with Amortized Inference For Deep Learning Recommendation Models, by Lars Hertel et al.
Efficient user history modeling with amortized inference for deep learning recommendation modelsby Lars Hertel, Neil…
Summary of Sequential Compression Layers For Efficient Federated Learning in Foundational Models, by Navyansh Mahla et al.
Sequential Compression Layers for Efficient Federated Learning in Foundational Modelsby Navyansh Mahla, Sunny Gupta, Amit…
Summary of Innovative Sentiment Analysis and Prediction Of Stock Price Using Finbert, Gpt-4 and Logistic Regression: a Data-driven Approach, by Olamilekan Shobayo et al.
Innovative Sentiment Analysis and Prediction of Stock Price Using FinBERT, GPT-4 and Logistic Regression: A…
Summary of Toward Non-invasive Diagnosis Of Bankart Lesions with Deep Learning, by Sahil Sethi et al.
Toward Non-Invasive Diagnosis of Bankart Lesions with Deep Learningby Sahil Sethi, Sai Reddy, Mansi Sakarvadia,…
Summary of Feature Group Tabular Transformer: a Novel Approach to Traffic Crash Modeling and Causality Analysis, by Oscar Lares et al.
Feature Group Tabular Transformer: A Novel Approach to Traffic Crash Modeling and Causality Analysisby Oscar…
Summary of Understanding Factual Recall in Transformers Via Associative Memories, by Eshaan Nichani et al.
Understanding Factual Recall in Transformers via Associative Memoriesby Eshaan Nichani, Jason D. Lee, Alberto BiettiFirst…
Summary of Policy Agnostic Rl: Offline Rl and Online Rl Fine-tuning Of Any Class and Backbone, by Max Sobol Mark et al.
Policy Agnostic RL: Offline RL and Online RL Fine-Tuning of Any Class and Backboneby Max…
Summary of Inverting Visual Representations with Detection Transformers, by Jan Rathjens et al.
Inverting Visual Representations with Detection Transformersby Jan Rathjens, Shirin Reyhanian, David Kappel, Laurenz WiskottFirst submitted…
Summary of Normalizing Flows Are Capable Generative Models, by Shuangfei Zhai et al.
Normalizing Flows are Capable Generative Modelsby Shuangfei Zhai, Ruixiang Zhang, Preetum Nakkiran, David Berthelot, Jiatao…
Summary of Curse Of Attention: a Kernel-based Perspective For Why Transformers Fail to Generalize on Time Series Forecasting and Beyond, by Yekun Ke et al.
Curse of Attention: A Kernel-Based Perspective for Why Transformers Fail to Generalize on Time Series…