Guillaume Lajoie

27 papers · 2019–2025 · 4 venues · across top CS/AI venues

Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.

Achievements

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🗺️ Taxonomy Completionist (40) 🏃 Academic Marathon · Sprint 🌍 Conference Polyglot · Bronze 🌉 Interdisciplinary Bridge · Bronze 🐣 Hot Topic Early Bird

👑 Triple Crown 🤝 Dynamic Duo (11) ⚡ Prolific Year · Productive 🌈 Renaissance Researcher (5) 💎 Century Club · Bronze ❓ The Questioner (2) 🗃️ Keyword Collector (137) 🔥 Unstoppable · Bronze

Venues

ICLR (13) NeurIPS (7) ICML (6) AISTATS (1)

Top co-authors

Yoshua Bengio (11) Eric Elmoznino (5) Sarthak Mittal (5) Blake Aaron Richards (4) Ezekiel Williams (3) Arna Ghosh (3) Giancarlo Kerg (3) Colin Bredenberg (3) Yuhan Helena Liu (3) Blake Richards (3)

Research topics

Machine Learning (22) Optimization & Theory (16) Deep Learning (15) Architectures (10) Artificial Intelligence (9) Core AI (7) Core Methods (7) Interdisciplinary (5) Learning Types · Machine Learning (4) Techniques (4) Cognitive Science (3) Learning Types · Deep Learning (3) Models (3) Science (3) Bayesian & Probabilistic (2)

Keywords

recurrent neural network (5) transformer architecture (3) neural network optimization (2) biological plausibility (2) few-shot learning (2) stochastic gradient descent (2) out-of-distribution generalization (2) in-context learning (2) synaptic plasticity (2) feature learning (2) gradient descent (2) dynamical system (2) generative flow network (2) vanishing gradient (2) representation learning (2) attention mechanism (2) neuromorphic computing (2) transfer learning (1) image generation (1) contrastive learning (1)

Papers

Accelerating Training with Neuron Interaction and Nowcasting Networks ICLR 2025 Does learning the right latent variables necessarily improve in-context learning? ICML 2025 Expressivity of Neural Networks with Random Weights and Learned Biases ICLR 2025 In-Context Learning and Occam’s Razor ICML 2025 Multi-agent cooperation through learning-aware policy gradients ICLR 2025 Towards a Formal Theory of Representational Compositionality ICML 2025 Amortizing intractable inference in large language models ICLR 2024 Delta-AI: Local objectives for amortized inference in sparse graphical models ICLR 2024 How connectivity structure shapes rich and lazy learning in neural circuits ICLR 2024 Leveraging Unpaired Data for Vision-Language Generative Models via Cycle Consistency ICLR 2024 Sufficient conditions for offline reactivation in recurrent neural networks ICLR 2024 Synaptic Weight Distributions Depend on the Geometry of Plasticity ICLR 2024 A Unified, Scalable Framework for Neural Population Decoding NeurIPS 2023 Flexible Phase Dynamics for Bio-Plausible Contrastive Learning ICML 2023 Formalizing locality for normative synaptic plasticity models NeurIPS 2023 How gradient estimator variance and bias impact learning in neural networks ICLR 2023 Reliability of CKA as a Similarity Measure in Deep Learning ICLR 2023 Beyond accuracy: generalization properties of bio-plausible temporal credit assignment rules NeurIPS 2022 Compositional Attention: Disentangling Search and Retrieval ICLR 2022 Continuous-Time Meta-Learning with Forward Mode Differentiation ICLR 2022 Is a Modular Architecture Enough? NeurIPS 2022 Multi-scale Feature Learning Dynamics: Insights for Double Descent ICML 2022 Gradient Starvation: A Learning Proclivity in Neural Networks NeurIPS 2021 Implicit Regularization via Neural Feature Alignment AISTATS 2021 Learning to Combine Top-Down and Bottom-Up Signals in Recurrent Neural Networks with Attention over Modules ICML 2020 Untangling tradeoffs between recurrence and self-attention in artificial neural networks NeurIPS 2020 Non-normal Recurrent Neural Network (nnRNN): learning long time dependencies while improving expressivity with transient dynamics NeurIPS 2019