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Predictive Sampling with Forecasting Autoregressive Models
v1v2 (latest)

Predictive Sampling with Forecasting Autoregressive Models

International Conference on Machine Learning (ICML), 2020
23 February 2020
Auke Wiggers
Emiel Hoogeboom
    BDL
ArXiv (abs)PDFHTML

Papers citing "Predictive Sampling with Forecasting Autoregressive Models"

12 / 12 papers shown
DeepPCR: Parallelizing Sequential Operations in Neural Networks
DeepPCR: Parallelizing Sequential Operations in Neural NetworksNeural Information Processing Systems (NeurIPS), 2023
Federico Danieli
Miguel Sarabia
Xavier Suau
Yuan-Sen Ting
Luca Zappella
266
6
0
28 Sep 2023
Accelerating Large Language Model Decoding with Speculative Sampling
Accelerating Large Language Model Decoding with Speculative Sampling
Charlie Chen
Sebastian Borgeaud
G. Irving
Jean-Baptiste Lespiau
Laurent Sifre
J. Jumper
BDLLRM
451
796
0
02 Feb 2023
ELF: Exact-Lipschitz Based Universal Density Approximator Flow
ELF: Exact-Lipschitz Based Universal Density Approximator Flow
Achintya Gopal
196
1
0
13 Dec 2021
PixelPyramids: Exact Inference Models from Lossless Image Pyramids
PixelPyramids: Exact Inference Models from Lossless Image Pyramids
Shweta Mahajan
Stefan Roth
TPM
260
2
0
17 Oct 2021
Autoregressive Diffusion Models
Autoregressive Diffusion Models
Emiel Hoogeboom
Alexey A. Gritsenko
Jasmijn Bastings
Ben Poole
Rianne van den Berg
Tim Salimans
DiffM
649
217
0
05 Oct 2021
A Review of the Gumbel-max Trick and its Extensions for Discrete
  Stochasticity in Machine Learning
A Review of the Gumbel-max Trick and its Extensions for Discrete Stochasticity in Machine Learning
Iris A. M. Huijben
W. Kool
Max B. Paulus
Ruud J. G. van Sloun
476
136
0
04 Oct 2021
Parallel and Flexible Sampling from Autoregressive Models via Langevin
  Dynamics
Parallel and Flexible Sampling from Autoregressive Models via Langevin DynamicsInternational Conference on Machine Learning (ICML), 2021
V. Jayaram
John Thickstun
DiffM
299
26
0
17 May 2021
Parallelized Rate-Distortion Optimized Quantization Using Deep Learning
Parallelized Rate-Distortion Optimized Quantization Using Deep LearningIEEE International Workshop on Multimedia Signal Processing (MMSP), 2020
D. Kianfar
Auke Wiggers
A. Said
Reza Pourreza
Taco S. Cohen
MQ
151
2
0
11 Dec 2020
Locally Masked Convolution for Autoregressive Models
Locally Masked Convolution for Autoregressive Models
Ajay Jain
Pieter Abbeel
Deepak Pathak
DiffMOffRL
253
32
0
22 Jun 2020
Denoising Diffusion Probabilistic Models
Denoising Diffusion Probabilistic Models
Jonathan Ho
Ajay Jain
Pieter Abbeel
DiffM
6.2K
29,328
0
19 Jun 2020
The Convolution Exponential and Generalized Sylvester Flows
The Convolution Exponential and Generalized Sylvester FlowsNeural Information Processing Systems (NeurIPS), 2020
Emiel Hoogeboom
Victor Garcia Satorras
Jakub M. Tomczak
Max Welling
309
30
0
02 Jun 2020
Accelerating Feedforward Computation via Parallel Nonlinear Equation
  Solving
Accelerating Feedforward Computation via Parallel Nonlinear Equation SolvingInternational Conference on Machine Learning (ICML), 2020
Yang Song
Chenlin Meng
Renjie Liao
Stefano Ermon
362
44
0
10 Feb 2020
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