Differentiable Programming @NeurIPSConf

Joined July 2021
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Exciting-looking program by @createaiplans today! Starts shortly; tune in!
The day we've all been waiting for has finally arrived! Join us today from 7am-6pm EST for a workshop full of possibilities at the intersection of programming languages and neurosymbolism. Brought to you in part by @Mila_Quebec, @NeurIPSConf and ML/PL enthusiasts just like you!
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Differentiable Programming retweeted
The day we've all been waiting for has finally arrived! Join us today from 7am-6pm EST for a workshop full of possibilities at the intersection of programming languages and neurosymbolism. Brought to you in part by @Mila_Quebec, @NeurIPSConf and ML/PL enthusiasts just like you!
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The penultimate talk for the day: Gordon Plotkin on complete axiomatization of forward differentiation.
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We just finished the last invited talk for the day: Thank you, Harshitha Menon for your talk on approximate high performance computing guided by AD!
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Nacime Bouziani spoke about a foreign function interface for the Unified Form Language [UFL]! See the paper here: arxiv.org/pdf/2111.00945.pdf
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Pleasure to host Karen Liu speaking about learnable physics models!
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Wow, the day flew by! We are about the start the last session in less than 10 min. Come join us for talks by @sokrypton, Harshitha Menon, Gordon Plotkin, and Bhupalee Kalita!
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We just kicked off our next session! Excited to hear from @PatrickHeimbach, Karen Liu, Nacime Bouziani, and @alexanderklew!
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We are about to start the poster session very soon! Come join us in Gather Town! eventhosts.gather.town/app/d…
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And @KenoFischer just finished his talk on Diffractor.jl: a next-generation, compiler-based AD system for Julia. Check out his code from today here bit.ly/3ymDjMr
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Cool talk by @FrankNoeBerlin about Differentiable Programming in Molecular Physics!
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Our next session is in 10min! Tune in for talks by Frank Noe (@FrankNoeBerlin), Keno Fischer (@KenoFischer), Patrick Kidger (@PatrickKidger), and Deniz Bezgin!
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Awesome talk by @yuaanzhou about SYMPAIS: SYMbolic Parallel Adaptive Importance Sampling for Probabilistic Program Analysis. Check out the paper here dl.acm.org/doi/10.1145/34682…!
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