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RECOMBINER: Robust and Enhanced Compression with Bayesian Implicit Neural Representations
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RECOMBINER: Robust and Enhanced Compression with Bayesian Implicit Neural Representations

Carlos Rombaldo Junior
Ingolf Becker
Zongyu Guo
Shane Johnson
ArXiv (abs)PDFHTMLGithub (11★)

Papers citing "RECOMBINER: Robust and Enhanced Compression with Bayesian Implicit Neural Representations"

14 / 14 papers shown
Title
Towards Lossless Implicit Neural Representation via Bit Plane Decomposition
Towards Lossless Implicit Neural Representation via Bit Plane Decomposition
Woo Kyoung Han
Byeonghun Lee
Hyunmin Cho
Sunghoon Im
Kyong Hwan Jin
MQ
451
0
0
28 Feb 2025
Good, Cheap, and Fast: Overfitted Image Compression with Wasserstein Distortion
Good, Cheap, and Fast: Overfitted Image Compression with Wasserstein Distortion
Jona Ballé
Luca Versari
Emilien Dupont
Hyunjik Kim
Matthias Bauer
DiffM
171
1
0
30 Nov 2024
Bidirectional Consistency Models
Bidirectional Consistency Models
Liangchen Li
Jiajun He
DiffM
108
13
0
26 Mar 2024
Instant Neural Graphics Primitives with a Multiresolution Hash Encoding
Instant Neural Graphics Primitives with a Multiresolution Hash Encoding
Thomas Müller
Alex Evans
Christoph Schied
A. Keller
327
4,037
0
16 Jan 2022
LoRA: Low-Rank Adaptation of Large Language Models
LoRA: Low-Rank Adaptation of Large Language Models
J. E. Hu
Yelong Shen
Phillip Wallis
Zeyuan Allen-Zhu
Yuanzhi Li
Shean Wang
Lu Wang
Weizhu Chen
OffRLAI4TSAI4CEALMAIMat
471
10,367
0
17 Jun 2021
What Are Bayesian Neural Network Posteriors Really Like?
What Are Bayesian Neural Network Posteriors Really Like?
Pavel Izmailov
Sharad Vikram
Matthew D. Hoffman
A. Wilson
UQCVBDL
72
385
0
29 Apr 2021
Causal Contextual Prediction for Learned Image Compression
Causal Contextual Prediction for Learned Image Compression
Zongyu Guo
Zhizheng Zhang
Runsen Feng
Zhibo Chen
CML
54
141
0
19 Nov 2020
Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains
Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains
Matthew Tancik
Pratul P. Srinivasan
B. Mildenhall
Sara Fridovich-Keil
N. Raghavan
Utkarsh Singhal
R. Ramamoorthi
Jonathan T. Barron
Ren Ng
124
2,421
0
18 Jun 2020
Implicit Neural Representations with Periodic Activation Functions
Implicit Neural Representations with Periodic Activation Functions
Vincent Sitzmann
Julien N. P. Martel
Alexander W. Bergman
David B. Lindell
Gordon Wetzstein
AI4TS
153
2,556
0
17 Jun 2020
Efficient and Scalable Bayesian Neural Nets with Rank-1 Factors
Efficient and Scalable Bayesian Neural Nets with Rank-1 Factors
Michael W. Dusenberry
Ghassen Jerfel
Yeming Wen
Yi-An Ma
Jasper Snoek
Katherine A. Heller
Balaji Lakshminarayanan
Dustin Tran
UQCVBDL
57
213
0
14 May 2020
Minimal Random Code Learning: Getting Bits Back from Compressed Model Parameters
Minimal Random Code Learning: Getting Bits Back from Compressed Model Parameters
Marton Havasi
Robert Peharz
José Miguel Hernández-Lobato
63
82
0
30 Sep 2018
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Chelsea Finn
Pieter Abbeel
Sergey Levine
OOD
823
11,909
0
09 Mar 2017
Variational Dropout and the Local Reparameterization Trick
Variational Dropout and the Local Reparameterization Trick
Diederik P. Kingma
Tim Salimans
Max Welling
BDL
226
1,514
0
08 Jun 2015
UCF101: A Dataset of 101 Human Actions Classes From Videos in The Wild
UCF101: A Dataset of 101 Human Actions Classes From Videos in The Wild
K. Soomro
Amir Zamir
M. Shah
CLIPVGen
152
6,148
0
03 Dec 2012

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