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ORCIDEkdeep Singh Lubana
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2020 – today
- 2024
[c18]Eric J. Bigelow, Ekdeep Singh Lubana, Robert P. Dick, Hidenori Tanaka, Tomer D. Ullman:
In-Context Learning Dynamics with Random Binary Sequences. ICLR 2024- [c17]Samyak Jain, Robert Kirk, Ekdeep Singh Lubana, Robert P. Dick, Hidenori Tanaka, Tim Rocktäschel, Edward Grefenstette, David Scott Krueger:
Mechanistically analyzing the effects of fine-tuning on procedurally defined tasks. ICLR 2024 - [c16]Mikail Khona, Maya Okawa, Jan Hula, Rahul Ramesh, Kento Nishi, Robert P. Dick, Ekdeep Singh Lubana, Hidenori Tanaka:
Towards an Understanding of Stepwise Inference in Transformers: A Synthetic Graph Navigation Model. ICML 2024 - [c15]Rahul Ramesh, Ekdeep Singh Lubana, Mikail Khona, Robert P. Dick, Hidenori Tanaka:
Compositional Capabilities of Autoregressive Transformers: A Study on Synthetic, Interpretable Tasks. ICML 2024 - [i20]Mikail Khona, Maya Okawa, Jan Hula, Rahul Ramesh, Kento Nishi, Robert P. Dick, Ekdeep Singh Lubana, Hidenori Tanaka:
Towards an Understanding of Stepwise Inference in Transformers: A Synthetic Graph Navigation Model. CoRR abs/2402.07757 (2024) - [i19]Usman Anwar, Abulhair Saparov, Javier Rando, Daniel Paleka, Miles Turpin, Peter Hase, Ekdeep Singh Lubana, Erik Jenner, Stephen Casper, Oliver Sourbut, Benjamin L. Edelman, Zhaowei Zhang, Mario Günther, Anton Korinek, José Hernández-Orallo, Lewis Hammond, Eric J. Bigelow, Alexander Pan, Lauro Langosco, Tomasz Korbak, Heidi Zhang, Ruiqi Zhong, Seán Ó hÉigeartaigh, Gabriel Recchia, Giulio Corsi, Alan Chan, Markus Anderljung, Lilian Edwards, Yoshua Bengio, Danqi Chen, Samuel Albanie, Tegan Maharaj, Jakob N. Foerster, Florian Tramèr, He He, Atoosa Kasirzadeh, Yejin Choi, David Krueger:
Foundational Challenges in Assuring Alignment and Safety of Large Language Models. CoRR abs/2404.09932 (2024) - [i18]Core Francisco Park, Maya Okawa, Andrew Lee, Ekdeep Singh Lubana, Hidenori Tanaka:
Emergence of Hidden Capabilities: Exploring Learning Dynamics in Concept Space. CoRR abs/2406.19370 (2024) - [i17]Samyak Jain, Ekdeep Singh Lubana, Kemal Oksuz, Tom Joy, Philip H. S. Torr, Amartya Sanyal, Puneet K. Dokania:
What Makes and Breaks Safety Fine-tuning? A Mechanistic Study. CoRR abs/2407.10264 (2024) - [i16]Ekdeep Singh Lubana, Kyogo Kawaguchi, Robert P. Dick, Hidenori Tanaka:
A Percolation Model of Emergence: Analyzing Transformers Trained on a Formal Language. CoRR abs/2408.12578 (2024) - [i15]Yongyi Yang, Core Francisco Park, Ekdeep Singh Lubana, Maya Okawa, Wei Hu, Hidenori Tanaka:
Dynamics of Concept Learning and Compositional Generalization. CoRR abs/2410.08309 (2024) - 2023
- [c14]Ziyin Liu, Ekdeep Singh Lubana, Masahito Ueda, Hidenori Tanaka:
What shapes the loss landscape of self supervised learning? ICLR 2023 - [c13]Ekdeep Singh Lubana, Eric J. Bigelow, Robert P. Dick, David Scott Krueger, Hidenori Tanaka:
Mechanistic Mode Connectivity. ICML 2023: 22965-23004 - [c12]Maya Okawa, Ekdeep Singh Lubana, Robert P. Dick, Hidenori Tanaka:
Compositional Abilities Emerge Multiplicatively: Exploring Diffusion Models on a Synthetic Task. NeurIPS 2023 - [c11]Cindy Wu, Ekdeep Singh Lubana, Bruno Kacper Mlodozeniec, Robert Kirk, David Krueger:
What Mechanisms Does Knowledge Distillation Distill? UniReps 2023: 60-75 - [i14]Maya Okawa, Ekdeep Singh Lubana, Robert P. Dick, Hidenori Tanaka:
Compositional Abilities Emerge Multiplicatively: Exploring Diffusion Models on a Synthetic Task. CoRR abs/2310.09336 (2023) - [i13]Eric J. Bigelow, Ekdeep Singh Lubana, Robert P. Dick, Hidenori Tanaka, Tomer D. Ullman:
In-Context Learning Dynamics with Random Binary Sequences. CoRR abs/2310.17639 (2023) - [i12]Samyak Jain, Robert Kirk, Ekdeep Singh Lubana, Robert P. Dick, Hidenori Tanaka, Edward Grefenstette, Tim Rocktäschel, David Scott Krueger:
Mechanistically analyzing the effects of fine-tuning on procedurally defined tasks. CoRR abs/2311.12786 (2023) - [i11]Rahul Ramesh, Mikail Khona, Robert P. Dick, Hidenori Tanaka, Ekdeep Singh Lubana:
How Capable Can a Transformer Become? A Study on Synthetic, Interpretable Tasks. CoRR abs/2311.12997 (2023) - [i10]Ekdeep Singh Lubana, Johann Brehmer, Pim de Haan, Taco Cohen:
FoMo Rewards: Can we cast foundation models as reward functions? CoRR abs/2312.03881 (2023) - 2022
- [c10]Ekdeep Singh Lubana, Puja Trivedi, Danai Koutra, Robert P. Dick:
How do Quadratic Regularizers Prevent Catastrophic Forgetting: The Role of Interpolation. CoLLAs 2022: 819-837 - [c9]Ekdeep Singh Lubana, Chi Ian Tang, Fahim Kawsar, Robert P. Dick, Akhil Mathur:
Orchestra: Unsupervised Federated Learning via Globally Consistent Clustering. ICML 2022: 14461-14484 - [c8]Puja Trivedi, Ekdeep Singh Lubana, Mark Heimann, Danai Koutra, Jayaraman J. Thiagarajan:
Analyzing Data-Centric Properties for Graph Contrastive Learning. NeurIPS 2022 - [c7]Puja Trivedi, Ekdeep Singh Lubana, Yujun Yan
, Yaoqing Yang, Danai Koutra:
Augmentations in Graph Contrastive Learning: Current Methodological Flaws & Towards Better Practices. WWW 2022: 1538-1549 - [i9]Ekdeep Singh Lubana, Chi Ian Tang, Fahim Kawsar, Robert P. Dick, Akhil Mathur:
Orchestra: Unsupervised Federated Learning via Globally Consistent Clustering. CoRR abs/2205.11506 (2022) - [i8]Puja Trivedi, Ekdeep Singh Lubana, Mark Heimann, Danai Koutra, Jayaraman J. Thiagarajan:
Analyzing Data-Centric Properties for Contrastive Learning on Graphs. CoRR abs/2208.02810 (2022) - [i7]Ziyin Liu, Ekdeep Singh Lubana, Masahito Ueda, Hidenori Tanaka:
What shapes the loss landscape of self-supervised learning? CoRR abs/2210.00638 (2022) - [i6]Ekdeep Singh Lubana, Eric J. Bigelow, Robert P. Dick, David Scott Krueger, Hidenori Tanaka:
Mechanistic Mode Connectivity. CoRR abs/2211.08422 (2022) - 2021
- [c6]Ekdeep Singh Lubana, Robert P. Dick:
A Gradient Flow Framework For Analyzing Network Pruning. ICLR 2021 - [c5]Ekdeep Singh Lubana, Robert P. Dick, Hidenori Tanaka:
Beyond BatchNorm: Towards a Unified Understanding of Normalization in Deep Learning. NeurIPS 2021: 4778-4791 - [i5]Ekdeep Singh Lubana, Puja Trivedi, Robert P. Dick:
Rethinking Quadratic Regularizers: Explicit Movement Regularization for Continual Learning. CoRR abs/2102.02805 (2021) - [i4]Ekdeep Singh Lubana, Robert P. Dick, Hidenori Tanaka:
Beyond BatchNorm: Towards a General Understanding of Normalization in Deep Learning. CoRR abs/2106.05956 (2021) - [i3]Puja Trivedi, Ekdeep Singh Lubana, Yujun Yan, Yaoqing Yang, Danai Koutra:
Augmentations in Graph Contrastive Learning: Current Methodological Flaws & Towards Better Practices. CoRR abs/2111.03220 (2021) - 2020
- [c4]Benjamin Simpson, Ekdeep Singh Lubana, Yuchen Liu, Robert P. Dick:
Intelligent Scene Caching to Improve Accuracy for Energy-Constrained Embedded Vision. CVPR Workshops 2020: 3114-3122 - [i2]Ekdeep Singh Lubana, Puja Trivedi, Conrad D. Hougen, Robert P. Dick, Alfred O. Hero III:
OrthoReg: Robust Network Pruning Using Orthonormality Regularization. CoRR abs/2009.05014 (2020) - [i1]Ekdeep Singh Lubana, Robert P. Dick:
A Gradient Flow Framework For Analyzing Network Pruning. CoRR abs/2009.11839 (2020)
2010 – 2019
- 2019
- [c3]Ekdeep Singh Lubana, Vinayak Aggarwal, Robert P. Dick:
Machine Foveation: An Application-Aware Compressive Sensing Framework. DCC 2019: 478-487 - [c2]Ekdeep Singh Lubana, Robert P. Dick, Vinayak Aggarwal, Pyari Mohan Pradhan:
Minimalistic Image Signal Processing for Deep Learning Applications. ICIP 2019: 4165-4169 - 2018
- [j1]Ekdeep Singh Lubana, Robert P. Dick:
Digital Foveation: An Energy-Aware Machine Vision Framework. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 37(11): 2371-2380 (2018) - [c1]Ekdeep Singh Lubana, Mangesh Gurav, Maryam Shojaei Baghini:
Snap: Chlorophyll Concentration Calculator Using RAW Images of Leaves. IEEE SENSORS 2018: 1-4
Coauthor Index
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