Max Patacchiola

CEO @ Sapiente Education | ex-{University of Cambridge, University of Edinburgh, Snapchat, Huawei, Tools for Humanity}

[Alex Blania @alexblania]

it's been too long.

https://t.co/NIkM785gbV

[World @worldnetwork]

"It is essential to place the human person at the heart of all our concerns and activities."

[World @worldnetwork]

It's a new world. Join project co-inventors Alex Blania & Sam Altman next week to learn more.

[Max Patacchiola @mpatacch]

I'll be in San Francisco on Monday to attend the @OpenAI DevDay. Excited to know what's next for ChatGPT and DALL-E. Reach out if you are around and want to have a chat.

[Cambridge MLG @CambridgeMLG]

We're at #ICLR23 and excited to share our work! We have got 15 papers, including 6 orals – see our schedule below, and please come talk to us and our fantastic collaborators :)

[Cambridge MLG @CambridgeMLG]

We've got 21(!) workshop papers at #NeurIPS2022! Come by Friday, Saturday and next week to talk to us if any of the topics below seem interesting. We're always happy to talk about our work.

Our members have also been hard at work organising some of these workshops...

[Cambridge MLG @CambridgeMLG]

We're at @NeurIPSConf in New Orleans with 14 papers! Come and have a chat with us and our fantastic collaborators :D See our #NeurIPS2022 schedule below!

[Max Patacchiola @mpatacch]

Our latest paper has been accepted at NeurIPS 2022. We propose a new layer called CaSE that can rapidly adapt a neural net to unseen datasets in the few-shot setting.

Hope to meet many of you in New Orleans!

arxiv: https://t.co/SHOvDMiilU
Github: https://t.co/7cN06jRyYh

[DeepAI @DeepAI]

Contextual Squeeze-and-Excitation for Efficient Few-Shot Image Classification
https://t.co/trtuHBv6Do
by @mpatacch et al.
#NeuralNetwork #ComputerScience

[DeepAI @DeepAI]

FiT: Parameter Efficient Few-shot Transfer Learning for Personalized and Federated Image Classification
https://t.co/3iCQd7uwXs
by Aliaksandra Shysheya et al. including @mpatacch
#NaiveBayesClassifiers #DeepLearning

[Cambridge MLG @CambridgeMLG]

We're excited to be at #ICLR2022 this week! Our group and collaborators will be presenting 11 papers (including an Oral and 3 Spotlights) at the main conference!
Check out our @iclr_conf schedule below. Please drop by and have a chat.

[Max Patacchiola @mpatacch]

All of reality is being computed by a short computer program. Love this tiny artwork from a #tedtalk of @SchmidhuberAI. Author: @GuzelPoluektova

[Cambridge MLG @CambridgeMLG]

We're excited to be at #NeurIPS2021 this week! Our group will be presenting 22 papers at the main conference with 10 papers today! Check out our full @NeurIPS2021 schedule below.

[Daniela Massiceti @dannimassi]

Our paper “Memory Efficient Meta-Learning with Large Images" was accepted at #NeurIPS 2021! 🪄🪄 With John Bronskill, @mpatacch, @katjahofmann, @sebnowozin and Richard Turner @CambridgeMLG (1/6)

[Cambridge MLG @CambridgeMLG]

We're happy to present the CBL Alumni talk series!

🕑4-5pm BST every 2nd Friday

This week with @andrewgwils:
https://t.co/9CFya6Dkui

Next up: @markvanderwilk @shakir_za @DavidDuvenaud @FinaleDoshi @fhuszar

If you'd like to attend, please e-mail
[email protected]

[arXiv Daily @Arxiv_Daily]

How Sensitive are Meta-Learners to Dataset Imbalance?
https://t.co/WQxX7H34IB
by @OchalMateusz et al. including @mpatacch
#OpenSource #ComputerScience

[Cambridge MLG @CambridgeMLG]

We're happy to launch a brand-new blog today, feel free to check it out!

It's starting off with a great two-part post by @ikwess and Richard E. Turner, with many more interesting posts to come, on our group's research and beyond!

https://t.co/9x17TNTvHk

[Max Patacchiola @mpatacch]

@jcanore @MSFTResearchCam Cheers José!

[Max Patacchiola @mpatacch]

I am joining the University of Cambridge, Machine Learning Group, working with Richard Turner and @MSFTResearchCam to develop efficient, flexible, and robust machine learning methods for real-world applications.

[Max Patacchiola @mpatacch]

@d_hgarcia @MSFTResearchCam Thank you Daniel :-)