convolutional neural network – Andrew Fairless, Ph.D.

What I Read: Deep learning, single-cell sequencing

By Andrew Fairless on March 6, 2024January 25, 2024

https://thegradient.pub/deep-learning-for-single-cell-sequencing-a-microscope-to-uncover-the-rich-diversity-of-individual-cells/ Deep learning for single-cell sequencing: a microscope to see the diversity of cellsFatima Zahra El Hajji1/13/24 1:12 PM “…we will explore the pivotal role that Deep Learning, in particular,Continue readingWhat I Read: Deep learning, single-cell sequencing

What I Read: Sparse Networks

By Andrew Fairless on July 31, 2023June 15, 2023

https://www.quantamagazine.org/sparse-neural-networks-point-physicists-to-useful-data-20230608/ Sparse Networks Come to the Aid of Big PhysicsSteve NadisJune 8, 2023 “A novel type of neural network is helping physicists with the daunting challenge of data analysis.”

What I Read: Geometric Deep Learning

By Andrew Fairless on April 10, 2023February 22, 2023

https://thegradient.pub/towards-geometric-deep-learning/ Towards Geometric Deep LearningMichael Bronstein18.Feb.2023 “Geometric Deep Learning is an umbrella term for approaches considering a broad class of ML problems from the perspectives of symmetry and invariance.”

What I Read: Realtime User Actions in Recommendation

By Andrew Fairless on February 27, 2023January 9, 2023

https://medium.com/pinterest-engineering/how-pinterest-leverages-realtime-user-actions-in-recommendation-to-boost-homefeed-engagement-volume-165ae2e8cde8 How Pinterest Leverages Realtime User Actions in Recommendation to Boost Homefeed Engagement VolumeXue Xia, Software Engineer, Homefeed Ranking; Neng Gu, Software Engineer, Content & User Understanding; Dhruvil Deven Badani,Continue readingWhat I Read: Realtime User Actions in Recommendation

What I Read: Zero-Shot, K-Shot Learning

By Andrew Fairless on October 18, 2022September 9, 2022

https://www.datature.io/blog/zero-shot-and-k-shot-learning Comprehensive Guide to Zero-Shot and K-Shot LearningLeonard SoAugust 23, 2022 “Few-shot learning is a type of supervised learning that is intended to rapidly generalise to new tasks containing onlyContinue readingWhat I Read: Zero-Shot, K-Shot Learning

What I Read: Transformers in computer vision

By Andrew Fairless on September 6, 2022August 3, 2022

https://theaisummer.com/transformers-computer-vision/ Transformers in computer vision: ViT architectures, tips, tricks and improvementsNikolas Adaloglouon2021-10-21 “You are probably already aware of the Vision Transformer (ViT)…. We will address questions like how can youContinue readingWhat I Read: Transformers in computer vision

What I Read: Visual Explanation of Classifiers

By Andrew Fairless on March 23, 2022February 3, 2022

https://ai.googleblog.com/2022/01/introducing-stylex-new-approach-for.html Introducing StylEx: A New Approach for Visual Explanation of ClassifiersTuesday, January 18, 2022Posted by Oran Lang and Inbar Mosseri, Software Engineers, Google Research“Previous approaches for visual explanations of classifiers…Continue readingWhat I Read: Visual Explanation of Classifiers

What I Read: AI Accelerators

By Andrew Fairless on February 28, 2022January 20, 2022

https://medium.com/@adi.fu7/ai-accelerators-part-ii-transistors-and-pizza-or-why-do-we-need-accelerators-75738642fdaa AI Accelerators — Part II: Transistors and Pizza (or: Why Do We Need Accelerators)?Adi FuchsDec 5 “There can not be a “one size fits all” approach when it comesContinue readingWhat I Read: AI Accelerators

What I Read: Dataset Distillation

By Andrew Fairless on February 9, 2022January 20, 2022

https://ai.googleblog.com/2021/12/training-machine-learning-models-more.html Training Machine Learning Models More Efficiently with Dataset DistillationWednesday, December 15, 2021Posted by Timothy Nguyen1, Research Engineer and Jaehoon Lee, Senior Research Scientist, Google Research“For a machine learning (ML)Continue readingWhat I Read: Dataset Distillation

What I Read: AI Researchers Fight Noise by Turning to Biology

By Andrew Fairless on February 1, 2022December 12, 2021

https://www.quantamagazine.org/ai-researchers-fight-noise-by-turning-to-biology-20211207/ AI Researchers Fight Noise by Turning to BiologyAllison WhittenContributing WriterDecember 7, 2021 “Tiny amounts of artificial noise can fool neural networks, but not humans. Some researchers are looking toContinue readingWhat I Read: AI Researchers Fight Noise by Turning to Biology

Tag: convolutional neural network