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Found 9 papers, 5 papers with code
Monte Carlo Tree Search for Interpreting Stress in Natural Language
Using a dataset of Reddit posts that exhibit stress, we demonstrate the ability of our MCTS algorithm to identify interpretable explanations for a person's feeling of stress in both a context-dependent and context-independent manner.
VMAF-based Bitrate Ladder Estimation for Adaptive Streaming
In HTTP Adaptive Streaming, video content is conventionally encoded by adapting its spatial resolution and quantization level to best match the prevailing network state and display characteristics.
Rationalizing Text Matching: Learning Sparse Alignments via Optimal Transport
Selecting input features of top relevance has become a popular method for building self-explaining models.
Uncertainty Quantification Using Neural Networks for Molecular Property Prediction
While we believe these results show that existing UQ methods are not sufficient for all common use-cases and demonstrate the benefits of further research, we conclude with a practical recommendation as to which existing techniques seem to perform well relative to others.
Improving Molecular Design by Stochastic Iterative Target Augmentation
The property predictor is then used as a likelihood model for filtering candidate structures from the generative model.
Iterative Target Augmentation for Effective Conditional Generation
Many challenging prediction problems, from molecular optimization to program synthesis, involve creating complex structured objects as outputs.
Deep Learning for Automated Classification and Characterization of Amorphous Materials
The characterization of amorphous materials is especially challenging because their lack of long-range order makes it difficult to define structural metrics.
Building a Production Model for Retrieval-Based Chatbots
Response suggestion is an important task for building human-computer conversation systems.
Analyzing Learned Molecular Representations for Property Prediction
In addition, we introduce a graph convolutional model that consistently matches or outperforms models using fixed molecular descriptors as well as previous graph neural architectures on both public and proprietary datasets.
Ranked #3 on
Molecular Property Prediction
on QM9
