Luke Melas-Kyriazi

According to our database1, Luke Melas-Kyriazi authored at least 21 papers between 2018 and 2024.

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

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
GES: Generalized Exponential Splatting for Efficient Radiance Field Rendering.
CoRR, 2024

IM-3D: Iterative Multiview Diffusion and Reconstruction for High-Quality 3D Generation.
CoRR, 2024

Fixed Point Diffusion Models.
CoRR, 2024

2023
Understanding Self-Supervised Features for Learning Unsupervised Instance Segmentation.
CoRR, 2023

A Benchmark for Learning to Translate a New Language from One Grammar Book.
CoRR, 2023

Augmenting medical image classifiers with synthetic data from latent diffusion models.
CoRR, 2023

The Harvard USPTO Patent Dataset: A Large-Scale, Well-Structured, and Multi-Purpose Corpus of Patent Applications.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

RealFusion 360° Reconstruction of Any Object from a Single Image.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

PC<sup>2</sup>: Projection-Conditioned Point Cloud Diffusion for Single-Image 3D Reconstruction.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Follow the Wisdom of the Crowd: Effective Text Generation via Minimum Bayes Risk Decoding.
Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

2022
Finding an Unsupervised Image Segmenter in each of your Deep Generative Models.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Prompt-and-Rerank: A Method for Zero-Shot and Few-Shot Arbitrary Textual Style Transfer with Small Language Models.
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

Deep Spectral Methods: A Surprisingly Strong Baseline for Unsupervised Semantic Segmentation and Localization.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021
Intrinisic Gradient Compression for Federated Learning.
CoRR, 2021

Do You Even Need Attention? A Stack of Feed-Forward Layers Does Surprisingly Well on ImageNet.
CoRR, 2021

PixMatch: Unsupervised Domain Adaptation via Pixelwise Consistency Training.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2020
The Mathematical Foundations of Manifold Learning.
CoRR, 2020

Show, Edit and Tell: A Framework for Editing Image Captions.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019
Encoder-Agnostic Adaptation for Conditional Language Generation.
CoRR, 2019

Generation-Distillation for Efficient Natural Language Understanding in Low-Data Settings.
Proceedings of the 2nd Workshop on Deep Learning Approaches for Low-Resource NLP, 2019

2018
Training for Diversity in Image Paragraph Captioning.
Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31, 2018


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