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Found 6 papers, 2 papers with code
Fine-tuning Protein Language Models with Deep Mutational Scanning improves Variant Effect Prediction
Protein Language Models (PLMs) have emerged as performant and scalable tools for predicting the functional impact and clinical significance of protein-coding variants, but they still lag experimental accuracy.
High Performance Hyperspectral Image Classification using Graphics Processing Units
We propose accelerated methods for the well-known recursive hierarchical segmentation (RHSEG) clustering method, using GPUs, hybrid multicore CPU with a GPU and hybrid multi-core CPU/GPU clusters.
Text Generation with Deep Variational GAN
Generating realistic sequences is a central task in many machine learning applications.
Improved and Efficient Text Adversarial Attacks using Target Information
There has been recently a growing interest in studying adversarial examples on natural language models in the black-box setting.
Explain2Attack: Text Adversarial Attacks via Cross-Domain Interpretability
Training robust deep learning models for down-stream tasks is a critical challenge.
OptiGAN: Generative Adversarial Networks for Goal Optimized Sequence Generation
One of the challenging problems in sequence generation tasks is the optimized generation of sequences with specific desired goals.
