Normalizing flows: An introduction and review of current methods I Kobyzev, SJD Prince, MA Brubaker IEEE transactions on pattern analysis and machine intelligence 43 (11), 3964 …, 2020 | 1238 | 2020 |
Representation Learning for Dynamic Graphs: A Survey SM Kazemi, R Goel, K Jain, I Kobyzev, A Sethi, P Forsyth, P Poupart Journal of Machine Learning Research 21 (70), 1-73, 2020 | 445 | 2020 |
Dylora: Parameter efficient tuning of pre-trained models using dynamic search-free low-rank adaptation M Valipour, M Rezagholizadeh, I Kobyzev, A Ghodsi arXiv preprint arXiv:2210.07558, 2022 | 54 | 2022 |
Tails of Lipschitz triangular flows P Jaini, I Kobyzev, Y Yu, M Brubaker International Conference on Machine Learning, 4673-4681, 2020 | 48 | 2020 |
Krona: Parameter efficient tuning with kronecker adapter A Edalati, M Tahaei, I Kobyzev, VP Nia, JJ Clark, M Rezagholizadeh arXiv preprint arXiv:2212.10650, 2022 | 42 | 2022 |
A short study on compressing decoder-based language models T Li, YE Mesbahi, I Kobyzev, A Rashid, A Mahmud, N Anchuri, ... arXiv preprint arXiv:2110.08460, 2021 | 21 | 2021 |
Polarized-VAE: Proximity based disentangled representation learning for text generation V Balasubramanian, I Kobyzev, H Bahuleyan, I Shapiro, O Vechtomova arXiv preprint arXiv:2004.10809, 2020 | 20 | 2020 |
Generating emotionally aligned responses in dialogues using affect control theory N Asghar, I Kobyzev, J Hoey, P Poupart, MB Sheikh arXiv preprint arXiv:2003.03645, 2020 | 17 | 2020 |
A categorical approach to cyclic cohomology of quasi-Hopf algebras and Hopf algebroids I Kobyzev, I Shapiro Applied Categorical Structures 27, 85-109, 2019 | 14 | 2019 |
Improving generalization of pre-trained language models via stochastic weight averaging P Lu, I Kobyzev, M Rezagholizadeh, A Rashid, A Ghodsi, P Langlais arXiv preprint arXiv:2212.05956, 2022 | 6 | 2022 |
Equivariant Discrete Normalizing Flows AJ Bose, I Kobyzev CoRR, 2021 | 6* | 2021 |
Anti-Yetter-Drinfeld modules for quasi-Hopf algebras I Kobyzev, I Shapiro Symmetry, Integrability and Geometry: Methods and Applications (SIGMA) 14 (098), 2018 | 6 | 2018 |
Continuation kd: Improved knowledge distillation through the lens of continuation optimization A Jafari, I Kobyzev, M Rezagholizadeh, P Poupart, A Ghodsi arXiv preprint arXiv:2212.05998, 2022 | 4 | 2022 |
A semi-holographic hyperdimensional representation system for hardware-friendly cognitive computing A Serb, I Kobyzev, J Wang, T Prodromakis Philosophical Transactions of the Royal Society A 378 (2164), 20190162, 2020 | 4 | 2020 |
Do we need Label Regularization to Fine-tune Pre-trained Language Models? I Kobyzev, A Jafari, M Rezagholizadeh, T Li, A Do-Omri, P Lu, P Poupart, ... arXiv preprint arXiv:2205.12428, 2022 | 3* | 2022 |
G-theory of root stacks and equivariant K-theory A Dhillon, I Kobyzev Annals of K-Theory 4 (2), 151-183, 2019 | 3 | 2019 |
Resonance RoPE: Improving Context Length Generalization of Large Language Models S Wang, I Kobyzev, P Lu, M Rezagholizadeh, B Liu arXiv preprint arXiv:2403.00071, 2024 | 1 | 2024 |
Hyperparameter optimization for Large Language Model instruction-tuning C Tribes, S Benarroch-Lelong, P Lu, I Kobyzev arXiv preprint arXiv:2312.00949, 2023 | 1 | 2023 |
Attribute controlled dialogue prompting R Liu, A Rashid, I Kobyzev, M Rezagholizadeh, P Poupart arXiv preprint arXiv:2307.05228, 2023 | 1 | 2023 |
Learning functions on multiple sets using multi-set transformers KA Selby, A Rashid, I Kobyzev, M Rezagholizadeh, P Poupart Uncertainty in Artificial Intelligence, 1760-1770, 2022 | 1 | 2022 |