Ke Li

Affiliations:
  • University of California, Berkeley, USA


According to our database1, Ke Li authored at least 27 papers between 2015 and 2023.

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Bibliography

2023
How Good Are Deep Generative Models for Solving Inverse Problems?
CoRR, 2023

PAPR: Proximity Attention Point Rendering.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Adaptive IMLE for Few-shot Pretraining-free Generative Modelling.
Proceedings of the International Conference on Machine Learning, 2023

2022
CHIMLE: Conditional Hierarchical IMLE for Multimodal Conditional Image Synthesis.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Multimodal Shape Completion via Implicit Maximum Likelihood Estimation.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2022

2021
Shape Completion via IMLE.
CoRR, 2021

Cascading Modular Network (CAM-Net) for Multimodal Image Synthesis.
CoRR, 2021

2020
Multimodal Image Synthesis with Conditional Implicit Maximum Likelihood Estimation.
Int. J. Comput. Vis., 2020

Better Knowledge Retention through Metric Learning.
CoRR, 2020

Generating Unobserved Alternatives.
CoRR, 2020

Inclusive GAN: Improving Data and Minority Coverage in Generative Models.
Proceedings of the Computer Vision - ECCV 2020, 2020

2019
Advances in Machine Learning: Nearest Neighbour Search, Learning to Optimize and Generative Modelling.
PhD thesis, 2019

Trajectory Normalized Gradients for Distributed Optimization.
CoRR, 2019

Approximate Feature Collisions in Neural Nets.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Diverse Image Synthesis From Semantic Layouts via Conditional IMLE.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

Non-Adversarial Image Synthesis With Generative Latent Nearest Neighbors.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

2018
Are All Training Examples Created Equal? An Empirical Study.
CoRR, 2018

On the Implicit Assumptions of GANs.
CoRR, 2018

Super-Resolution via Conditional Implicit Maximum Likelihood Estimation.
CoRR, 2018

Implicit Maximum Likelihood Estimation.
CoRR, 2018

2017
Learning to Optimize Neural Nets.
CoRR, 2017

Fast k-Nearest Neighbour Search via Prioritized DCI.
Proceedings of the 34th International Conference on Machine Learning, 2017

Learning to Optimize.
Proceedings of the 5th International Conference on Learning Representations, 2017

2016
Fast k-Nearest Neighbour Search via Dynamic Continuous Indexing.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Amodal Instance Segmentation.
Proceedings of the Computer Vision - ECCV 2016, 2016

Iterative Instance Segmentation.
Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition, 2016

2015
Bandit Label Inference for Weakly Supervised Learning.
CoRR, 2015


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