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Volodymyr Kuleshov
17 papers at tracked venues · 13 at CORE A* · active 2024–2025
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Venues
NeurIPS
×5
ICML
×4
UAI
×3
ICLR
×2
AAAI
×1
AISTATS
×1
CVPR
×1
Frequent coauthors
Aaron Gokaslan
×8
Subham S. Sahoo
×6
Yair Schiff
×6
Marianne Arriola
×3
Justin T. Chiu
×3
Shachi Deshpande
×3
Guanghan Wang
×3
Charles Marx
×2
Hao Phung
×2
Christopher De Sa
×2
Zhihan Yang
×1
Zhixuan Qi
×1
Papers
Block Diffusion: Interpolating Between Autoregressive and Diffusion Language Models
BibTeX ⧉
ICLR 2025
·
Marianne Arriola
,
Aaron Gokaslan
,
Justin T. Chiu
,
Zhihan Yang
,
Zhixuan Qi
,
Jiaqi Han
,
Subham Sekhar Sahoo
,
Volodymyr Kuleshov
Calibrated Regression Against An Adversary Without Regret
BibTeX ⧉
UAI 2025
·
Shachi Deshpande
,
Charles Marx
,
Volodymyr Kuleshov
Denoising Diffusion Variational Inference: Diffusion Models as Expressive Variational Posteriors
BibTeX ⧉
AAAI 2025
·
Wasu Top Piriyakulkij
,
Yingheng Wang
,
Volodymyr Kuleshov
Encoder-Decoder Diffusion Language Models for Efficient Training and Inference
BibTeX ⧉
NeurIPS 2025
·
Marianne Arriola
,
Yair Schiff
,
Hao Phung
,
Aaron Gokaslan
,
Volodymyr Kuleshov
Remasking Discrete Diffusion Models with Inference-Time Scaling
BibTeX ⧉
NeurIPS 2025
·
Guanghan Wang
,
Yair Schiff
,
Subham S. Sahoo
,
Volodymyr Kuleshov
Simple Guidance Mechanisms for Discrete Diffusion Models
BibTeX ⧉
ICLR 2025
·
Yair Schiff
,
Subham Sekhar Sahoo
,
Hao Phung
,
Guanghan Wang
,
Sam Boshar
,
Hugo Dalla-torre
,
Bernardo P. de Almeida
,
Alexander M. Rush
,
Thomas Pierrot
,
Volodymyr Kuleshov
The Diffusion Duality
BibTeX ⧉
ICML 2025
·
Subham Sekhar Sahoo
,
Justin Deschenaux
,
Aaron Gokaslan
,
Guanghan Wang
,
Justin T. Chiu
,
Volodymyr Kuleshov
Caduceus: Bi-Directional Equivariant Long-Range DNA Sequence Modeling
BibTeX ⧉
ICML 2024
·
Yair Schiff
,
Chia-Hsiang Kao
,
Aaron Gokaslan
,
Tri Dao
,
Albert Gu
,
Volodymyr Kuleshov
Calibrated and Conformal Propensity Scores for Causal Effect Estimation
BibTeX ⧉
UAI 2024
·
Shachi Deshpande
,
Volodymyr Kuleshov
Common Canvas: Open Diffusion Models Trained on Creative-Commons Images
BibTeX ⧉
CVPR 2024
·
Aaron Gokaslan
,
A. Feder Cooper
,
Jasmine Collins
,
Landan Seguin
,
Austin Jacobson
,
Mihir Patel
,
Jonathan Frankle
,
Cory Stephenson
,
Volodymyr Kuleshov
Diffusion Models With Learned Adaptive Noise
BibTeX ⧉
NeurIPS 2024
·
Subham S. Sahoo
,
Aaron Gokaslan
,
Christopher De Sa
,
Volodymyr Kuleshov
DySLIM: Dynamics Stable Learning by Invariant Measure for Chaotic Systems
BibTeX ⧉
ICML 2024
·
Yair Schiff
,
Zhong Yi Wan
,
Jeffrey B. Parker
,
Stephan Hoyer
,
Volodymyr Kuleshov
,
Fei Sha
,
Leonardo Zepeda-Núñez
Local Discovery by Partitioning: Polynomial-Time Causal Discovery Around Exposure-Outcome Pairs
BibTeX ⧉
UAI 2024
·
Jacqueline R. M. A. Maasch
,
Weishen Pan
,
Shantanu Gupta
,
Volodymyr Kuleshov
,
Kyra Gan
,
Fei Wang
Online Calibrated and Conformal Prediction Improves Bayesian Optimization
BibTeX ⧉
AISTATS 2024
·
Shachi Deshpande
,
Charles Marx
,
Volodymyr Kuleshov
QuIP#: Even Better LLM Quantization with Hadamard Incoherence and Lattice Codebooks
BibTeX ⧉
ICML 2024
·
Albert Tseng
,
Jerry Chee
,
Qingyao Sun
,
Volodymyr Kuleshov
,
Christopher De Sa
Simple and Effective Masked Diffusion Language Models
BibTeX ⧉
NeurIPS 2024
·
Subham S. Sahoo
,
Marianne Arriola
,
Yair Schiff
,
Aaron Gokaslan
,
Edgar Marroquin
,
Justin T. Chiu
,
Alexander Rush
,
Volodymyr Kuleshov
The GAN is dead; long live the GAN! A Modern GAN Baseline
BibTeX ⧉
NeurIPS 2024
·
Nick Huang
,
Aaron Gokaslan
,
Volodymyr Kuleshov
,
James Tompkin