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Latest Posts – Sander Dieleman

 Gegenereerd op Maart 16 2026 18:21 PM

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Latest Posts – Sander Dieleman

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locale en_US
type article
title Latest Posts
description Describe this nonsense.
url https://sander.ai/
site_name Sander Dieleman

Headings

H1 H2 H3 H4 H5 H6
6 44 24 1 0 0
  • [H1] Sander Dieleman
  • [H1] Generative modelling in latent space
  • [H1] Diffusion is spectral autoregression
  • [H1] Noise schedules considered harmful
  • [H1] The paradox of diffusion distillation
  • [H1] The geometry of diffusion guidance
  • [H2] Latest Posts
  • [H2] The recipe
  • [H2] How we got here
  • [H2] Why two stages?
  • [H2] Trading off reconstruction quality and modelability
  • [H2] Controlling capacity
  • [H2] Curating and shaping the latent space
  • [H2] The tyranny of the grid
  • [H2] Latents for other modalities
  • [H2] Will end-to-end win in the end?
  • [H2] Closing thoughts
  • [H2] Acknowledgements
  • [H2] References
  • [H2] Two forms of iterative refinement
  • [H2] A spectral view of diffusion
  • [H2] What about sound?
  • [H2] Unstable equilibrium
  • [H2] Closing thoughts
  • [H2] Acknowledgements
  • [H2] References
  • [H2] Noise schedules: a whirlwind tour
  • [H2] Noise levels: focusing on what matters
  • [H2] Model design choices: what might tip the balance?
  • [H2] Noise schedules are a superfluous abstraction
  • [H2] Adaptive weighting mechanisms
  • [H2] Closing thoughts
  • [H2] Acknowledgements
  • [H2] References
  • [H2] Diffusion sampling: tread carefully!
  • [H2] Moving through input space with purpose
  • [H2] Diffusion distillation
  • [H2] But what about “no free lunch”?
  • [H2] Do we really need a teacher?
  • [H2] Charting the maze between data and noise
  • [H2] Closing thoughts
  • [H2] Acknowledgements
  • [H2] References
  • [H2] A word of warning about high-dimensional spaces
  • [H2] Visualising diffusion sampling
  • [H2] Classifier guidance
  • [H2] Classifier-free guidance
  • [H2] Closing thoughts
  • [H2] Acknowledgements
  • [H2] References
  • [H3] Latent autoregression
  • [H3] Latent diffusion
  • [H3] VQGAN and KL-regularised latents
  • [H3] Tweaking reconstruction losses
  • [H3] Representation learning vs. reconstruction
  • [H3] Regularising for modelability
  • [H3] Diffusion all the way down
  • [H3] Image spectra
  • [H3] Noisy image spectra
  • [H3] Diffusion
  • [H3] Which frequencies are modelled at which noise levels?
  • [H3] Model output parameterisation \(\color{purple}{f(\mathbf{x}_t, t)}\)
  • [H3] Loss weighting \(\color{blue}{w(t)}\)
  • [H3] Time step distribution \(\color{red}{p(t)}\)
  • [H3] Time step spacing
  • [H3] Distilling diffusion sampling into a single forward pass
  • [H3] Progressive distillation
  • [H3] Guidance distillation
  • [H3] Rectified flow
  • [H3] Consistency distillation & TRACT
  • [H3] BOOT: data-free distillation
  • [H3] Sampling with neural operators
  • [H3] Score distillation sampling
  • [H3] Adversarial distillation
  • [H4] Sander Dieleman

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DeepMind Extern doFollow
April 15, 2025 Intern doFollow
Sander Dieleman Intern doFollow
latent variables Extern doFollow
The recipe Intern doFollow
How we got here Intern doFollow
Why two stages? Intern doFollow
Trading off reconstruction quality and modelability Intern doFollow
Controlling capacity Intern doFollow
Curating and shaping the latent space Intern doFollow
The tyranny of the grid Intern doFollow
Latents for other modalities Intern doFollow
Will end-to-end win in the end? Intern doFollow
Closing thoughts Intern doFollow
Acknowledgements Intern doFollow
References Intern doFollow
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my blog post on typicality Intern doFollow
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Test of Time award at NeurIPS 2024 Extern doFollow
https://t.co/Ochh17IvGx Extern doFollow
November 28, 2024 Extern doFollow
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Aurora model Extern doFollow
GPT-4o Extern doFollow
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Adam optimiser Extern doFollow
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Stable Diffusion Extern doFollow
DALL-E 2 Extern doFollow
Imagen 2 Extern doFollow
DALL-E 3 Extern doFollow
Imagen 3 Extern doFollow
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my previous blog post on noise schedules Intern doFollow
casting diffusion as autoregression in frequency space Intern doFollow
auditory masking Extern doFollow
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I tried to explain this on Twitter Extern doFollow
rate-distortion theory Extern doFollow
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entropy coding Extern doFollow
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arithmetic coding Extern doFollow
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EQ-VAE paper Extern doFollow
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Tupper’s self-referential formula Extern doFollow
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an extensive exploration Extern doFollow
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my previous blog post Intern doFollow
VQGAN paper Extern doFollow
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a latent generative modelling paper Extern doFollow
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April 14, 2025 Extern doFollow
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AuraEquiVAE Extern doFollow
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diffusion distillation Intern doFollow
consistency decoder Extern doFollow
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motion estimation Extern doFollow
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Twitter Extern doFollow
BlueSky Extern doFollow
The Unreasonable Effectiveness of Deep Features as a Perceptual Metric Extern doFollow
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Generative Adversarial Nets Extern doFollow
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Pixel recurrent neural networks Extern doFollow
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WaveNet: A Generative Model for Raw Audio Extern doFollow
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SampleRNN: An Unconditional End-to-End Neural Audio Generation Model Extern doFollow
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Adam: A Method for Stochastic Optimization Extern doFollow
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GIVT: Generative Infinite-Vocabulary Transformers Extern doFollow
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Autoregressive Image Generation without Vector Quantization Extern doFollow
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Symbolic Music Generation with Diffusion Models Extern doFollow
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Score-based Generative Modeling in Latent Space Extern doFollow
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High-Resolution Image Synthesis with Latent Diffusion Models Extern doFollow
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Generating Images with Sparse Representations Extern doFollow
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Transframer: Arbitrary Frame Prediction with Generative Models Extern doFollow
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JPEG-LM: LLMs as Image Generators with Canonical Codec Representations Extern doFollow
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Flow to the Mode: Mode-Seeking Diffusion Autoencoders for State-of-the-Art Image Tokenization Extern doFollow
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DINOv2: Learning Robust Visual Features without Supervision Extern doFollow
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Vector Quantized Contrastive Predictive Coding for Template-based Music Generation Extern doFollow
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AudioLM: a Language Modeling Approach to Audio Generation Extern doFollow
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How Should We Extract Discrete Audio Tokens from Self-Supervised Models? Extern doFollow
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SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis Extern doFollow
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A Theory of Usable Information Under Computational Constraints Extern doFollow
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LARP: Tokenizing Videos with a Learned Autoregressive Generative Prior Extern doFollow
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When Worse is Better: Navigating the compression-generation tradeoff in visual tokenization Extern doFollow
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Reconstruction vs. Generation: Taming Optimization Dilemma in Latent Diffusion Models Extern doFollow
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Masked Autoencoders Are Effective Tokenizers for Diffusion Models Extern doFollow
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Alias-Free Latent Diffusion Models: Improving Fractional Shift Equivariance of Diffusion Latent Space Extern doFollow
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Sample what you cant compress Extern doFollow
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Epsilon-VAE: Denoising as Visual Decoding Extern doFollow
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One-D-Piece: Image Tokenizer Meets Quality-Controllable Compression Extern doFollow
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FlexTok: Resampling Images into 1D Token Sequences of Flexible Length Extern doFollow
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“Principal Components” Enable A New Language of Images Extern doFollow
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CAT: Content-Adaptive Image Tokenization Extern doFollow
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Tokenize Image as a Set Extern doFollow
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Visual Lexicon: Rich Image Features in Language Space Extern doFollow
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Byte Latent Transformer: Patches Scale Better Than Tokens Extern doFollow
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Language modeling via stochastic processes Extern doFollow
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PLANNER: Generating Diversified Paragraph via Latent Language Diffusion Model Extern doFollow
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available on YouTube Extern doFollow
a Python notebook Extern doFollow
Two forms of iterative refinement Intern doFollow
A spectral view of diffusion Intern doFollow
What about sound? Intern doFollow
Unstable equilibrium Intern doFollow
flow-based models Extern doFollow
adversarial models Extern doFollow
an earlier blog post Intern doFollow
written about it before Intern doFollow
Fourier transform Extern doFollow
Imagenette dataset Extern doFollow
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pink noise Extern doFollow
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Rissanen et al. (2022) Extern doFollow
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Nyquist frequency Extern doFollow
Audio clip 1 Intern doFollow
Audio clip 2 Intern doFollow
Audio clip 3 Intern doFollow
Audio clip 4 Intern doFollow
GTZAN music/speech dataset Extern doFollow
green noise Extern doFollow
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phase information is typically discarded Intern doFollow
mel scale Extern doFollow
Riffusion Extern doFollow
https://t.co/Akv8aZl8Rv Extern doFollow
December 15, 2022 Extern doFollow
mel-frequency cepstral coefficients (MFCCs) Extern doFollow
discrete cosine transform (DCT) Extern doFollow
classifier-free guidance Intern doFollow
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Tian et al. (2024) Extern doFollow
Mattar et al. (2024) Extern doFollow
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pic.twitter.com/XSxP27pKSt Extern doFollow
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Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow Extern doFollow
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Simple and Effective Masked Diffusion Language Models Extern doFollow
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Simplified and Generalized Masked Diffusion for Discrete Data Extern doFollow
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FIFO-Diffusion: Generating Infinite Videos from Text without Training Extern doFollow
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Diffusion Forcing: Next-token Prediction Meets Full-Sequence Diffusion Extern doFollow
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Diffusion models are autoencoders Intern doFollow
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Noise levels: focusing on what matters Intern doFollow
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Adaptive weighting mechanisms Intern doFollow
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blog post Intern doFollow
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“Continuous diffusion for categorical data” Extern doFollow
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inverse transform sampling Extern doFollow
“Continuous Diffusion for Mixed-Type Tabular Data” Extern doFollow
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Santos & Lin (2023) Extern doFollow
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Fisher Information Extern doFollow
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Diffusion sampling: tread carefully! Intern doFollow
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Progressive distillation Intern doFollow
Guidance distillation Intern doFollow
Rectified flow Intern doFollow
Consistency distillation & TRACT Intern doFollow
BOOT: data-free distillation Intern doFollow
Sampling with neural operators Intern doFollow
Score distillation sampling Intern doFollow
Adversarial distillation Intern doFollow
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Charting the maze between data and noise Intern doFollow
an in-depth blog post Intern doFollow
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various perspectives on diffusion Intern doFollow
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previously discussed Intern doFollow
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Guidance: a cheat code for diffusion models Intern doFollow
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compelling results Extern doFollow
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ProlificDreamer: High-Fidelity and Diverse Text-to-3D Generation with Variational Score Distillation Extern doFollow
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Diff-Instruct: A Universal Approach for Transferring Knowledge From Pre-trained Diffusion Models Extern doFollow
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StyleGAN-T: Unlocking the Power of GANs for Fast Large-Scale Text-to-Image Synthesis Extern doFollow
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