Search Results for author:
Found 9 papers, 5 papers with code
Neural networks for abstraction and reasoning: Towards broad generalization in machines
We present the Perceptual Abstraction and Reasoning Language (PeARL) language, which allows DreamCoder to solve ARC tasks, and propose a new recognition model that allows us to significantly improve on the previous best implementation. We also propose a new encoding and augmentation scheme that allows large language models (LLMs) to solve ARC tasks, and find that the largest models can solve some ARC tasks.
Architectural Backdoors in Neural Networks
Machine learning is vulnerable to adversarial manipulation.
Single-cell Subcellular Protein Localisation Using Novel Ensembles of Diverse Deep Architectures
Unravelling protein distributions within individual cells is key to understanding their function and state and indispensable to developing new treatments.
Predicting the Ordering of Characters in Japanese Historical Documents
A major research project has been to make these historical documents accessible and understandable.
KaoKore: A Pre-modern Japanese Art Facial Expression Dataset
From classifying handwritten digits to generating strings of text, the datasets which have received long-time focus from the machine learning community vary greatly in their subject matter.
Learning to Localize Temporal Events in Large-scale Video Data
We address temporal localization of events in large-scale video data, in the context of the Youtube-8M Segments dataset.
Deep Learning for Classical Japanese Literature
Much of machine learning research focuses on producing models which perform well on benchmark tasks, in turn improving our understanding of the challenges associated with those tasks.
Ranked #4 on
Image Classification
on Kuzushiji-MNIST
(Error metric)
Deep Architectures and Ensembles for Semantic Video Classification
This work addresses the problem of accurate semantic labelling of short videos.
Cultivating DNN Diversity for Large Scale Video Labelling
We investigate factors controlling DNN diversity in the context of the Google Cloud and YouTube-8M Video Understanding Challenge.
