Probability theory, Probability distribution, Operations research, Generative, Probability density function, Random variable
RT @OpenAI: Progress towards stable and scalable training of energy-based models:
💻Blog: https://t.co/gMo8g5sctT
📝Paper: https://t.co/F9UlHf8JzI
🔤Code: https://t.co/WGIOX4OKxZ https://t.co/6TaoNQtljZ
OpenImplicit Generation and Generalization Methods for Energy-Based Models
We've made progress towards stable and scalable training of energy-based models [http://yann.lecun.com/exdb/publis/pdf/lecun-06.pdf] (EBMs) resulting in better sample quality and ...
RT @OpenAI: Progress towards stable and scalable training of energy-based models:
💻Blog: https://t.co/gMo8g5sctT
📝Paper: https://t.co/F9UlHf8JzI
🔤Code: https://t.co/WGIOX4OKxZ https://t.co/6TaoNQtljZ
OpenImplicit Generation and Generalization Methods for Energy-Based Models
We've made progress towards stable and scalable training of energy-based models [http://yann.lecun.com/exdb/publis/pdf/lecun-06.pdf] (EBMs) resulting in better sample quality and ...
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Flow-based Deep Generative Models
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Play with Generated Adversarial Networks (GANs) in your browser!
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24 NUMA-Caffe: NUMA-Aware Deep Learning Neural Networks PROBIR ROY, College of William and Mary SHUAIWEN LEON SONG, Pacific Northwest National Laboratory and College of William and Mary ...
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A partial list includes Fukunaga [97], Duda and Hart [77], Vapnik and Chervonenkis [233], Devijver and Kittler [70], Vapnik [229,230], Breiman, Friedman, Olshen, and Stone [53], Natarajan ...
