Black Forest Labs' new Self-Flow technique makes training multimodal AI models 2.8x more efficient

This efficiency makes it viable for enterprises to move beyond generic off-the-shelf solutions and develop specialized models ...
IEEE

RAEncoder: A Label-Free Reversible Adversarial Examples Encoder for Dataset Intellectual Property Protection

Abstract: Reversible Adversarial Examples (RAE) are designed to protect the intellectual property of datasets. Such examples can function as imperceptible adversarial examples to erode the model ...
IEEE

Encoder-Free Multiaxis Physics-Aware Fusion Network for Remote Sensing Image Dehazing

Abstract: Current methods for remote sensing image dehazing confront noteworthy computational intricacies and yield suboptimal dehazed outputs, thereby circumscribing their pragmatic applicability. To ...
eLife

Adaptive behavior is guided by integrated representations of controlled and non-controlled information

This useful study uses creative scalp EEG decoding methods to attempt to demonstrate that two forms of learned associations in a Stroop task are dissociable, despite sharing similar temporal dynamics.
eLife

Adaptive behavior is guided by integrated representations of controlled and non-controlled information

Department of Psychological and Brain Sciences, University of Iowa, Iowa City, United States Cognitive Control Collaborative, University of Iowa, Iowa City, United States Princeton Neuroscience ...
GitHub

smiles-encoder: One-hot encoding for simple molecular-input line-entry system (SMILES) strings

smiles-encoder is a Python package used to generate one-hot vectors representing SMILES strings (each string element is a one-hot vector). To contribute to smiles-encoder, make a pull request.
GitHub

TfELM : Extreme Learning Machines Framework with Python and TensorFlow

This framework provides a comprehensive set of tools and utilities for implementing and experimenting with Extreme Learning Machines using Python and TensorFlow. ELMs are a type of machine learning ...