Yongxin Yang

Orcid: 0000-0003-4134-8559

According to our database1, Yongxin Yang authored at least 105 papers between 2014 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
MixStyle Neural Networks for Domain Generalization and Adaptation.
Int. J. Comput. Vis., 2024

Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language Models.
CoRR, 2024

2023
SERF: Fine-Grained Interactive 3D Segmentation and Editing with Radiance Fields.
CoRR, 2023

Optimisation-Based Multi-Modal Semantic Image Editing.
CoRR, 2023

Mixture of Normalizing Flows for European Option Pricing.
Proceedings of the Uncertainty in Artificial Intelligence, 2023

On Calibration of Mathematical Finance Models by Hypernetworks.
Proceedings of the Machine Learning and Knowledge Discovery in Databases: Applied Data Science and Demo Track, 2023

MEDFAIR: Benchmarking Fairness for Medical Imaging.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

ChiroDiff: Modelling chirographic data with Diffusion Models.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Batch-Ensemble Stochastic Neural Networks for Out-of-Distribution Detection.
Proceedings of the IEEE International Conference on Acoustics, 2023

Learning to Name Classes for Vision and Language Models.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Partial Index Tracking: A Meta-Learning Approach.
Proceedings of the Conference on Lifelong Learning Agents, 2023

2022
An Application-oblivious Memory Scheduling System for DNN Accelerators.
ACM Trans. Archit. Code Optim., 2022

Learning Generalisable Omni-Scale Representations for Person Re-Identification.
IEEE Trans. Pattern Anal. Mach. Intell., 2022

Region Proposal Network Pre-Training Helps Label-Efficient Object Detection.
CoRR, 2022

ZooD: Exploiting Model Zoo for Out-of-Distribution Generalization.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Residual Contrastive Learning for Image Reconstruction: Learning Transferable Representations from Noisy Images.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Loss Function Learning for Domain Generalization by Implicit Gradient.
Proceedings of the International Conference on Machine Learning, 2022

Augmented Sliced Wasserstein Distances.
Proceedings of the Tenth International Conference on Learning Representations, 2022

SketchODE: Learning neural sketch representation in continuous time.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Long-tail Recognition via Compositional Knowledge Transfer.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Towards Unsupervised Sketch-based Image Retrieval.
Proceedings of the 33rd British Machine Vision Conference 2022, 2022

2021
SRD: A Tree Structure Based Decoder for Online Handwritten Mathematical Expression Recognition.
IEEE Trans. Multim., 2021

Domain Adaptive Ensemble Learning.
IEEE Trans. Image Process., 2021

Toward Fine-Grained Sketch-Based 3D Shape Retrieval.
IEEE Trans. Image Process., 2021

Dynamic multi-period sparse portfolio selection model with asymmetric investors' sentiments.
Expert Syst. Appl., 2021

Residual Contrastive Learning for Joint Demosaicking and Denoising.
CoRR, 2021

Meta-Calibration: Meta-Learning of Model Calibration Using Differentiable Expected Calibration Error.
CoRR, 2021

EvoGrad: Efficient Gradient-Based Meta-Learning and Hyperparameter Optimization.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Incorporating Prior Financial Domain Knowledge into Neural Networks for Implied Volatility Surface Prediction.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Pinpointing the Memory Behaviors of DNN Training.
Proceedings of the IEEE International Symposium on Performance Analysis of Systems and Software, 2021

Domain Generalization with MixStyle.
Proceedings of the 9th International Conference on Learning Representations, 2021

Towards Stochastic Neural Network via Feature Distribution Calibration.
Proceedings of the IEEE International Conference on Data Mining, 2021

StyleMeUp: Towards Style-Agnostic Sketch-Based Image Retrieval.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Context-Aware Layout to Image Generation With Enhanced Object Appearance.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Vectorization and Rasterization: Self-Supervised Learning for Sketch and Handwriting.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

More Photos Are All You Need: Semi-Supervised Learning for Fine-Grained Sketch Based Image Retrieval.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Cloud2Curve: Generation and Vectorization of Parametric Sketches.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Tensor Composition Net for Visual Relationship Prediction.
Proceedings of the 32nd British Machine Vision Conference 2021, 2021

Domain Attention Consistency for Multi-Source Domain Adaptation.
Proceedings of the 32nd British Machine Vision Conference 2021, 2021

Simple and Effective Stochastic Neural Networks.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

Fine-Grained VR Sketching: Dataset and Insights.
Proceedings of the International Conference on 3D Vision, 2021

2020
Pixelor: a competitive sketching AI agent. so you think you can sketch?
ACM Trans. Graph., 2020

Sketch-a-Segmenter: Sketch-Based Photo Segmenter Generation.
IEEE Trans. Image Process., 2020

Tensor Composition Net for Visual Relationship Prediction.
CoRR, 2020

Flexible Dataset Distillation: Learn Labels Instead of Images.
CoRR, 2020

Online Meta-Critic Learning for Off-Policy Actor-Critic Methods.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

RelationNet2: Deep Comparison Network for Few-Shot Learning.
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

A Tree-Structured Decoder for Image-to-Markup Generation.
Proceedings of the 37th International Conference on Machine Learning, 2020

Diversity and Sparsity: A New Perspective on Index Tracking.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

Deep Clusteringwith Concrete K-Means.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

Deep Clustering for Domain Adaptation.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

Index tracking with differentiate asset selection.
Proceedings of the ICAIF '20: The First ACM International Conference on AI in Finance, 2020

Learning to Generate Novel Domains for Domain Generalization.
Proceedings of the Computer Vision - ECCV 2020, 2020

Sequential Learning for Domain Generalization.
Proceedings of the Computer Vision - ECCV 2020 Workshops, 2020

Differentiable Automatic Data Augmentation.
Proceedings of the Computer Vision - ECCV 2020, 2020

Adversarial Robustness of Open-Set Recognition: Face Recognition and Person Re-identification.
Proceedings of the Computer Vision - ECCV 2020 Workshops, 2020

BézierSketch: A Generative Model for Scalable Vector Sketches.
Proceedings of the Computer Vision - ECCV 2020, 2020

Solving Mixed-Modal Jigsaw Puzzle for Fine-Grained Sketch-Based Image Retrieval.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Stochastic Classifiers for Unsupervised Domain Adaptation.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Sketch Less for More: On-the-Fly Fine-Grained Sketch-Based Image Retrieval.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Cross-Modal Hierarchical Modelling for Fine-Grained Sketch Based Image Retrieval.
Proceedings of the 31st British Machine Vision Conference 2020, 2020

Deep Domain-Adversarial Image Generation for Domain Generalisation.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

Index Tracking with Cardinality Constraints: A Stochastic Neural Networks Approach.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

Towards 3D VR-Sketch to 3D Shape Retrieval.
Proceedings of the 8th International Conference on 3D Vision, 2020

2019
Minimum Connected Dominating Set Algorithms for Ad Hoc Sensor Networks.
Sensors, 2019

Deep clustering with concrete k-means.
CoRR, 2019

Gated deep neural networks for implied volatility surfaces.
CoRR, 2019

An Alternative Hybrid Time-Frequency Domain Approach Based on Fast Iterative Shrinkage-Thresholding Algorithm for Rotating Acoustic Source Identification.
IEEE Access, 2019

Feature-Critic Networks for Heterogeneous Domain Generalization.
Proceedings of the 36th International Conference on Machine Learning, 2019

Omni-Scale Feature Learning for Person Re-Identification.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

Robust Person Re-Identification by Modelling Feature Uncertainty.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

Goal-Driven Sequential Data Abstraction.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

Episodic Training for Domain Generalization.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

Generalizable Person Re-Identification by Domain-Invariant Mapping Network.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

Generalising Fine-Grained Sketch-Based Image Retrieval.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

Disjoint Label Space Transfer Learning with Common Factorised Space.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
Frankenstein: Learning Deep Face Representations Using Small Data.
IEEE Trans. Image Process., 2018

Sensitivity Analysis of Geometrical Parameters on the Aerodynamic Performance of Closed-Box Girder Bridges.
Sensors, 2018

Deep Comparison: Relation Columns for Few-Shot Learning.
CoRR, 2018

Deep Neural Decision Trees.
CoRR, 2018

Deep Multi-task Learning to Recognise Subtle Facial Expressions of Mental States.
Proceedings of the Computer Vision - ECCV 2018, 2018

Learning to Compare: Relation Network for Few-Shot Learning.
Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

Learning Deep Sketch Abstraction.
Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

Learning to Generalize: Meta-Learning for Domain Generalization.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Unifying Multi-domain Multitask Learning: Tensor and Neural Network Perspectives.
Proceedings of the Domain Adaptation in Computer Vision Applications., 2017

Knowledge sharing: from atomic to parametrised context and shallow to deep models.
PhD thesis, 2017

Weakly-Supervised Image Annotation and Segmentation with Objects and Attributes.
IEEE Trans. Pattern Anal. Mach. Intell., 2017

Sketch-a-Net: A Deep Neural Network that Beats Humans.
Int. J. Comput. Vis., 2017

Actor-Critic Sequence Training for Image Captioning.
CoRR, 2017

Learning to Learn: Meta-Critic Networks for Sample Efficient Learning.
CoRR, 2017

Trace Norm Regularised Deep Multi-Task Learning.
Proceedings of the 5th International Conference on Learning Representations, 2017

Deep Multi-task Representation Learning: A Tensor Factorisation Approach.
Proceedings of the 5th International Conference on Learning Representations, 2017

Deeper, Broader and Artier Domain Generalization.
Proceedings of the IEEE International Conference on Computer Vision, 2017

Attribute-Enhanced Face Recognition with Neural Tensor Fusion Networks.
Proceedings of the IEEE International Conference on Computer Vision, 2017

Gated Neural Networks for Option Pricing: Rationality by Design.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016
Unifying Multi-Domain Multi-Task Learning: Tensor and Neural Network Perspectives.
CoRR, 2016

Multivariate Regression on the Grassmannian for Predicting Novel Domains.
Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition, 2016

2015
Zero-Shot Domain Adaptation via Kernel Regression on the Grassmannian.
CoRR, 2015

Deep Neural Networks for Sketch Recognition.
CoRR, 2015

A Unified Perspective on Multi-Domain and Multi-Task Learning.
Proceedings of the 3rd International Conference on Learning Representations, 2015

Transductive Multi-class and Multi-label Zero-shot Learning.
CoRR, 2015

When Face Recognition Meets with Deep Learning: An Evaluation of Convolutional Neural Networks for Face Recognition.
Proceedings of the 2015 IEEE International Conference on Computer Vision Workshop, 2015

Sketch-a-Net that Beats Humans.
Proceedings of the British Machine Vision Conference 2015, 2015

2014
Weakly Supervised Learning of Objects, Attributes and Their Associations.
Proceedings of the Computer Vision - ECCV 2014, 2014

Transductive Multi-label Zero-shot Learning.
Proceedings of the British Machine Vision Conference, 2014


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