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Found 12 papers, 2 papers with code
MultiFix: Learning to Repair Multiple Errors by Optimal Alignment Learning
We consider the problem of learning to repair erroneous C programs by learning optimal alignments with correct programs.
MPruner: Optimizing Neural Network Size with CKA-Based Mutual Information Pruning
Pruning is a well-established model compression technique that reduces the size of neural networks while mathematically guaranteeing accuracy preservation.
Towards Efficient Formal Verification of Spiking Neural Network
The power consumption of AI has become a significant societal issue; in this context, spiking neural networks (SNNs) offer a promising solution.
DBHP: Trajectory Imputation in Multi-Agent Sports Using Derivative-Based Hybrid Prediction
Many spatiotemporal domains handle multi-agent trajectory data, but in real-world scenarios, collected trajectory data are often partially missing due to various reasons.
Contextual Sprint Classification in Soccer Based on Deep Learning
The analysis of high-intensity runs (or sprints) in soccer has long been a topic of interest for sports science researchers and practitioners.
Ball Trajectory Inference from Multi-Agent Sports Contexts Using Set Transformer and Hierarchical Bi-LSTM
As artificial intelligence spreads out to numerous fields, the application of AI to sports analytics is also in the spotlight.
SoccerCPD: Formation and Role Change-Point Detection in Soccer Matches Using Spatiotemporal Tracking Data
In fluid team sports such as soccer and basketball, analyzing team formation is one of the most intuitive ways to understand tactics from domain participants' point of view.
Neuro-Symbolic Regex Synthesis Framework via Neural Example Splitting
We tackle the problem of learning regexes faster from positive and negative strings by relying on a novel approach called `neural example splitting'.
SplitRegex: Faster Regex Synthesis via Neural Example Splitting
SplitRegex is a divided-and-conquer framework for learning target regexes; split (=divide) positive strings and infer partial regexes for multiple parts, which is much more accurate than the whole string inferring, and concatenate (=conquer) inferred regexes while satisfying negative strings.
6MapNet: Representing soccer players from tracking data by a triplet network
Although the values of individual soccer players have become astronomical, subjective judgments still play a big part in the player analysis.
SoftRegex: Generating Regex from Natural Language Descriptions using Softened Regex Equivalence
We continue the study of generating se-mantically correct regular expressions from natural language descriptions (NL).
Neural Sign Language Translation based on Human Keypoint Estimation
Using the KETI sign language dataset, we develop a neural network model for translating sign videos into natural language sentences by utilizing the human keypoints extracted from a face, hands, and body parts.
