Inverting face embeddings with convolutional neural networks. - Andrey Zhmoginov; Mark Sandler 002 (CoRR, 2016)

The Power of Sparsity in Convolutional Neural Networks. - Soravit Changpinyo; Mark Sandler 002; Andrey Zhmoginov (CoRR, 2017)

CycleGAN, a Master of Steganography. - Casey Chu; Andrey Zhmoginov; Mark Sandler 002 (CoRR, 2017)

MobileNetV2: Inverted Residuals and Linear Bottlenecks. - Mark Sandler 002; Andrew G. Howard; Menglong Zhu; Andrey Zhmoginov; Liang-Chieh Chen (CVPR, 2018)

Inverted Residuals and Linear Bottlenecks: Mobile Networks for Classification, Detection and Segmentation. - Mark Sandler 002; Andrew G. Howard; Menglong Zhu; Andrey Zhmoginov; Liang-Chieh Chen (CoRR, 2018)

Non-Discriminative Data or Weak Model? On the Relative Importance of Data and Model Resolution. - Mark Sandler 002; Jonathan Baccash; Andrey Zhmoginov; Andrew Howard 002 (ICCV Workshops, 2019)

K for the Price of 1: Parameter-efficient Multi-task and Transfer Learning. - Pramod Kaushik Mudrakarta; Mark Sandler 002; Andrey Zhmoginov; Andrew G. Howard (ICLR (Poster), 2019)

Information-Bottleneck Approach to Salient Region Discovery. - Andrey Zhmoginov; Ian Fischer; Mark Sandler 002 (ECML/PKDD (3), 2020)

Image segmentation via Cellular Automata. - Mark Sandler 002; Andrey Zhmoginov; Liangcheng Luo; Alexander Mordvintsev; Ettore Randazzo; Blaise Agüera y Arcas (CoRR, 2020)

Large-Scale Generative Data-Free Distillation. - Liangchen Luo; Mark Sandler 002; Zi Lin; Andrey Zhmoginov; Andrew Howard 002 (CoRR, 2020)

BasisNet: Two-Stage Model Synthesis for Efficient Inference. - Mingda Zhang; Chun-Te Chu; Andrey Zhmoginov; Andrew Howard 002; Brendan Jou; Yukun Zhu; Li Zhang 003; Rebecca Hwa; Adriana Kovashka (CVPR Workshops, 2021)

Meta-Learning Bidirectional Update Rules. - Mark Sandler 002; Max Vladymyrov; Andrey Zhmoginov; Nolan Miller; Tom Madams; Andrew Jackson 004; Blaise Agüera y Arcas (ICML, 2021)

Compositional Models: Multi-Task Learning and Knowledge Transfer with Modular Networks. - Andrey Zhmoginov; Dina Bashkirova; Mark Sandler 002 (CoRR, 2021)

Fine-tuning Image Transformers using Learnable Memory. - Mark Sandler 002; Andrey Zhmoginov; Max Vladymyrov; Andrew Jackson 004 (CVPR, 2022)

HyperTransformer: Model Generation for Supervised and Semi-Supervised Few-Shot Learning. - Andrey Zhmoginov; Mark Sandler 002; Maksym Vladymyrov (ICML, 2022)

Decentralized Learning with Multi-Headed Distillation. - Andrey Zhmoginov; Mark Sandler 002; Nolan Miller; Gus Kristiansen; Max Vladymyrov (CVPR, 2023)

Transformers Learn In-Context by Gradient Descent. - Johannes von Oswald; Eyvind Niklasson; Ettore Randazzo; João Sacramento; Alexander Mordvintsev; Andrey Zhmoginov; Max Vladymyrov (ICML, 2023)

Training trajectories, mini-batch losses and the curious role of the learning rate. - Mark Sandler 002; Andrey Zhmoginov; Max Vladymyrov; Nolan Miller (CoRR, 2023)

Continual Few-Shot Learning Using HyperTransformers. - Max Vladymyrov; Andrey Zhmoginov; Mark Sandler 002 (CoRR, 2023)

Narrowing the Focus: Learned Optimizers for Pretrained Models. - Gus Kristiansen; Mark Sandler 002; Andrey Zhmoginov; Nolan Miller; Anirudh Goyal; Jihwan Lee; Max Vladymyrov (CoRR, 2024)

Learning and Unlearning of Fabricated Knowledge in Language Models. - Chen Sun; Nolan Andrew Miller; Andrey Zhmoginov; Max Vladymyrov; Mark Sandler 002 (CoRR, 2024)

Continual HyperTransformer: A Meta-Learner for Continual Few-Shot Learning. - Max Vladymyrov; Andrey Zhmoginov; Mark Sandler 002 (Trans. Mach. Learn. Res., 2024)

MELODI: Exploring Memory Compression for Long Contexts. - Yinpeng Chen; DeLesley Hutchins; Aren Jansen; Andrey Zhmoginov; David Racz; Jesper Sparre Andersen (ICLR, 2025)

How new data permeates LLM knowledge and how to dilute it. - Chen Sun; Renat Aksitov; Andrey Zhmoginov; Nolan Andrew Miller; Max Vladymyrov; Ulrich Rueckert; Been Kim; Mark Sandler 002 (ICLR, 2025)

Long Context In-Context Compression by Getting to the Gist of Gisting. - Aleksandar Petrov; Mark Sandler 002; Andrey Zhmoginov; Nolan Miller; Max Vladymyrov (CoRR, 2025)

Projectable Models: One-Shot Generation of Small Specialized Transformers from Large Ones. - Andrey Zhmoginov; Jihwan Lee; Mark Sandler 002 (CoRR, 2025)

Contextually Guided Transformers via Low-Rank Adaptation. - Andrey Zhmoginov; Jihwan Lee; Max Vladymyrov; Mark Sandler 002 (CoRR, 2025)