Tom Rainforth @tom_rainforth

Associate Professor in Machine Learning at the University of Oxford, Head of RainML Research Lab (https://t.co/uuBwQ2WdMN) robots.ox.ac.uk/~twgr/ Oxford, England Joined November 2016

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Jackson Atkins @JacksonAtkinsX

4 weeks ago

Apple and Oxford just made AI 6.5x better at problem-solving. The secret: it teaches AI agents to ask perfect questions. This rockets success rates from 14% to 91%. No need for fine-tuning or retraining. It runs on current models. Here's how it works: It's a strategic loop…

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Tom Rainforth @tom_rainforth

2 months ago

I have an opening for a 2-year postdoc in probabilistic machine learning and/or experimental design. The application deadline is the 3rd of September. See here for details and how to apply: tinyurl.com/rainmlpostdoc2…

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Tom Rainforth @tom_rainforth

a year ago

I have an opening for a 2.5-year postdoc position in the RainML lab as part of my ERC grant on probabilistic machine learning and intelligent data acquisition. Application deadline 10th July 2024. See here for details and to apply: tinyurl.com/rainmlpostdoc

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Tom Rainforth @tom_rainforth

a year ago

I'm delighted to announce that from September I will officially be an Associate Professor (remaining at the Oxford stats department)

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Tom Rainforth @tom_rainforth

a year ago

In-context learning can learn novel input-output relationships beyond what can be picked up from input context alone, but doesn't behave like conventional learning algorithm. Find out more at our ICLR poster #129 this afternoon. Paper: openreview.net/forum?id=YPIA7…, led by @janundnik

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Jannik Kossen @janundnik

a year ago

Are you at ICLR? Have you heard that In-Context Learning in LLMs does not learn label relationships? Well that's not true. Visit our poster TODAY to find out how LLMs incorporate label information. Spoiler: it's not Bayesian inference. Poster #129, May 7, 4.30 pm

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Tim Reichelt @TimReichelt3

a year ago

I will be presenting our work on "Beyond Bayesian Model Averaging over Paths in Probabilistic Programs with Stochastic Support" at AISTATS in Valencia tomorrow (details in thread below). If you are interested in probabilistic programming, come and say hi at poster session 1!

Tom Rainforth @tom_rainforth

2 years ago

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Freddie Bickford Smith @fbickfordsmith

a year ago

The current default recipe for Bayesian active learning doesn’t really work beyond MNIST scale. We suggest why that is and identify a simple fix. arxiv.org/abs/2404.17249 @aistats_conf with @AdamEFoster @tom_rainforth 1/5

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Christian Weilbach [email protected] @wh1lo

2 years ago

It is @NeurIPS time again! I am excited to present our trans-dimensional jump diffusion work with @AndrewC_ML @willarvey @ValentinDeBort1 @tom_rainforth and @ArnaudDoucet1 ! Come over on Thursday 2nd poster session, neurips.cc/virtual/2023/p…. arxiv.org/abs/2305.16261 #NeurIPS2023

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Yee Whye Teh @yeewhye

2 years ago

Interested in large language models? Worried about impacts of climate change? Come join us @oxcsml @NatureRecovery @UniofOxford in pushing the frontiers in #LLMs and at the same time help #NatureRecovery and address the impacts of #ClimateChange! bit.ly/4750IBO

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Jin Xu @jinxu06

2 years ago

We construct neural processes by iteratively transforming a simple stochastic process into an expressive one, similar to flow/diffusion-based models, but in function space! Join us at our #NeurIPS2023 poster session: neurips.cc/virtual/2023/p… on Wednesday morning!