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Found 8 papers, 4 papers with code
Uni-Mol Docking V2: Towards Realistic and Accurate Binding Pose Prediction
In recent years, machine learning (ML) methods have emerged as promising alternatives for molecular docking, offering the potential for high accuracy without incurring prohibitive computational costs.
Uni-SMART: Universal Science Multimodal Analysis and Research Transformer
Scientific literature often includes a wide range of multimodal elements, such as tables, charts, and molecule, which are hard for text-focused LLMs to understand and analyze.
SciAssess: Benchmarking LLM Proficiency in Scientific Literature Analysis
Recent breakthroughs in Large Language Models (LLMs) have revolutionized scientific literature analysis.
Pre-Training Protein Bi-level Representation Through Span Mask Strategy On 3D Protein Chains
In recent years, there has been a surge in the development of 3D structure-based pre-trained protein models, representing a significant advancement over pre-trained protein language models in various downstream tasks.
Computational framework for the generation of one-dimensional vascular models accounting for uncertainty in networks extracted from medical images
This raises the question, if we are building patient-specific models based on uncertain measurements, how accurate are the geometries we extract and how can we best represent a patient's vasculature?
Human Machine Co-adaption Interface via Cooperation Markov Decision Process System
Based on the proposed co-adaptive MDPs, the simulation study indicates the non-stationary problem can be mitigated using various proposed Policy Improvement approaches.
Model-based Reinforcement Learning
Multi-agent Reinforcement Learning
+2
Thinking Image Color Aesthetics Assessment: Models, Datasets and Benchmarks
We present a comprehensive study on a new task named image color aesthetics assessment (ICAA), which aims to assess color aesthetics based on human perception.
Data Assimilation Predictive GAN (DA-PredGAN): applied to determine the spread of COVID-19
To predict the spread of COVID-19 in an idealised town, we apply these methods to a compartmental model in epidemiology that is able to model space and time variations.
