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← Adversarial nets need neither Markov chains nor unrolled approximate…

3 connected korrents · 4 moments from 10 Jun 2014 to 10 Sept 2026.

Everything filed under GANs GANs Everything filed under product management product management Everything filed under LLMs LLMs Same subjectSame subjectSame subject Read this korrent: Adversarial nets need neither Markov chains nor unrolled approximate inference networks for training or sample generation. Adversarial nets need neither Markovchains nor unrolled approximate inferencenetworks for training or samplegeneration. Last stated 12 years ago 10 Jun 2014 YB Yoshua Bengio — holds since 2014-06-10 — tap for who they are Same subject: An adversarial GAN loss should only supplement a larger unsupervised or semi-supervised generative model rather than stand alone as a primary approach. — tap to centre the map on it An adversarial GAN loss should onlysupplement a larger unsupervised orsemi-supervised generative modelrather than stand alone as a primaryapproach. Last stated 6 years ago 4 Feb 2021 GW Gwern — holds since 2021-02-04 — tap for who they are Same subject: AI cannot turn an untested assumption into fact; that takes real customers and real data. — tap to centre the map on it AI cannot turn an untestedassumption into fact; that takesreal customers and real data. Last stated a month ago 10 Sept 2026 CV Claire Vo — holds since 2026-09-10 — tap for who they are Same subject: The knowledge a model soaks up in pre-training is holding it back; what we actually want is the intelligence with the knowledge stripped out. — tap to centre the map on it The knowledge a model soaks up inpre-training is holding it back;what we actually want is theintelligence with the knowledgestripped out. Last stated a year ago 17 Oct 2025 AK Andrej Karpathy — holds since 2025-10-17 — tap for who they are
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At the centre Adversarial nets need neither Markov chains nor unrolled approximate inference networks for training or sample generation. Last stated 10 Jun 2014 · 12 years ago Holds Yoshua Bengio Read this korrent →