Browsing: ML News
Machine Learning (ML) is everywhere these days, playing a crucial role in countless fields worldwide. Its applications are endless, and we rely on it more than…
RLHF is the standard approach for aligning LLMs. However, recent advances in offline alignment methods, such as direct preference optimization (DPO) and its variants, challenge the…
Artificial neural networks (ANNs) show a remarkable pattern when trained on natural data irrespective of exact initialization, dataset, or training objective; models trained on the same…
Pre-training large models on time series data faces several challenges: the lack of a comprehensive public time series repository, the complexity of diverse time series characteristics,…
In traffic management and urban planning, the ability to learn optimal routes from demonstrations conditioned on contextual features holds significant promise. As underscored by previous research…
A resurgence of interest in the computer automation of molecular design has occurred throughout the last five years, thanks to advancements in machine learning, especially generative…
Large language models (LLMs) such as GPT-4 and Llama are at the forefront of natural language processing, enabling various applications from automated chatbots to advanced text…
In the dynamic field of AI technology, a pressing challenge for the drug discovery (DD) community, especially in structural biology and computational chemistry, is the creation…
Anomaly detection has gained traction in various fields such as surveillance, medical analysis, and network security. Typically approached as a one-class classification problem, autoencoder (AE) models…
Molecular representation learning is an essential field focusing on understanding and predicting molecular properties through advanced computational models. It plays a significant role in drug discovery…