UH Manoa Weekly AI Seminar
SUBSCRIBE AI-SEMINAR firstname lastname
2025-04-04: EMMA: End-to-End Multimodal Model for Autonomous Driving, Hwang, et al. 2024 (presented by Moseli)
2025-03-28: T1-weighted MRI-based brain tumor classification using hybrid deep learning models, Ilani, et al. 2025 (presented by Chayanika), Global Inequalities in the Production of Artificial Intelligence: A Four-Country Study on Data Work, Casilli, et al. 2024 (presented by Kayla-Marie)
2025-03-14: LLM Processes: Numerical Predictive Distributions Conditioned on Natural Language Requeima, et al. 2024 (presented by Peter)
2025-03-07: Bayesian Flow Networks Graves, et al. 2024 (presented by Peter)
2025-02-28: Using Early Readouts to Mediate Featural Bias in Distillation Tiwari, et al. 2023 (presented by Amila)
2025-02-21: TimesNet: Temporal 2D-Variation Modeling for General Time Series Analysis Wu, et al. 2023 (presented by Linnea)
2025-02-14: Score-Based Generative Modeling Through Stochastic Differential Equations Song, et al. 2021 (presented by Yusuke)
2025-02-07: Inferring neural activity before plasticity as a foundation for learning beyond backpropagation Song, et al. 2024 (presented by Peter)
2025-01-31: DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning Guo, et al. 2025 (presented by Yosub)
2025-01-24: A theoretical design of concept sets: improving the predictability of concept bottleneck models Luyten and van der Schaar (presented by Arianna)
2025-01-17: Masked Siamese Networks for Label-Efficient Learning Assran, et al. 2022 (presented by Nick)
Todo: Aurora: A Foundation Model of the Atmosphere
Signup spreadsheet and site.
2024-12-06: Knowledge in the grey zone: AI and cybersecurity, Stevens, 2024 (presented by Chris),
OmniFold: A Method to Simultaneously Unfold All Observables, Andreassen, et al. 2020 (presented by Ethan),
Exposing Outlier Exposure: What Can Be Learned From Few, One, and Zero Outlier Images, Liznerski, et al. 2022 (presented by Tojo)
2024-11-15: Multimodal contrastive learning for remote sensing tasks, Jain, et al. 2022 (presented by Amila)
2024-11-08: Towards a Feminist Metaethics of AI, Siapka 2022 (presented by Kayla-Marie)
2024-11-01: SPECIAL IN-PERSON TALK (12-1pm): Lenore Pipes, Univ. of Hawaii Manoa
2024-10-25: On Learning to Think: Algorithmic Information Theory for Novel Combinations of Reinforcement Learning Controllers and Recurrent Neural World Models , Schmidhuber (presented by Peter)
2024-10-18: Hopfield Networks is All You Need, Ramsauer, et al. 2020 (presented by Peter)
2024-10-11: Physics-Informed Neural Networks for Multiphysics Data Assimilation with Application to Subsurface Transport He, et al. 2020 (presented by Kevin Egan)
2024-10-04: TALK: Karthika Mohan, Oregon State University, Causal Inference with Missing Data: Missingness Graphs, Recoverability and Testability (register here)
2024-09-27: Pygmalion Displacement: When Humanising AI Dehumanises Women, Erscoi, et al. (presented by Arianna)
2024-09-20: Generative Adversarial Nets, Goodfellow, et al. 2014 (Classic paper, presented by Zain)
2024-09-13: Stochastic Neural Network Symmetrisation in Markov Categories, Cornish (presented by Mitchell)
2024-09-06: SAM 2: Segment Anything in Images and Videos website, Ravi, et al. (presented by Joel)
2024-08-30: The Hidden Uniform Cluster Prior in Self-Supervised Learning, Assran, et al. (presented by Nick)
2024-08-27: SPECIAL IN-PERSON TALK (2pm in MSB 100): Michael Ito, University of Michigan, Learning Laplacian Positional Encodings for Heterophilous Graphs
2024-07-26: SPECIAL IN-PERSON TALK: Nikita Zhivotovskiy, Improving Risk Bounds with Unbounded Losses via Data-Dependent Priors.
2024-07-19: Generative Model by Estimating Gradients of the Data Distribution (presented by Yusuke Hatanaka)
2024-07-10: SPECIAL IN-PERSON TALK (11am in POST): Deva Ramanan, Perceiving and Understanding a Dynamic 3D World
2024-06-28: RankMe: Assessing the downstream performance of pretrained self-supervised representations by their rank (presented by Yannik Glaser)
2024-06-21: Transcendence: Generative Models Can Outperform The Experts That Train Them (presented by Mitchell Dennis)
2024-06-14: Ranks underlie outcome of combining classifiers: Quantitative roles for diversity and accuracy (presented by Arianna Bunnell)
2024-06-07: KL is All You Need (presented by Peter Sadowski)
2024-05-31: In What Ways Are Deep Neural Networks Invariant and How Should We Measure This? (presented by Yash Lodha)
2024-04-19: Stitchable Neural Networks (Amila leads)
2024-04-12: A Mathematical Framework for Transformer Circuits (Levi leads)
2024-04-05: TALK: Dusko Pavlovic
2024-03-15: TALK: Andrey Popov
2024-03-08: Superintelligence
2024-03-01: UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction (Arianna leads)
2024-02-16: MLP-Mixer: An All-MLP Architecture for Vision (Yosub leads)
2024-02-09: Revisiting the Calibration of Modern Neural Networks (Nick leads)
2024-02-02: 3D Gaussian Splatting (also check out blog post here; Peter leads)
2024-01-26: Sources of Uncertainty in ML: A Statistician’s View (Arianna leads)
2024-01-19: SPECIAL IN-PERSON TALK: Roberto Tamassia, Brown University, on Advances in Searchable Encryption
2023-12-01: Hyena Hierarchy: Towards Larger Convolutional Language Models, Poli, et al. 2023 (presented by Levi)
2023-11-17: GradMax: Growing Neural Networks using Gradient Information, Evci, et al. 2022 (presented by Amila)
2023-11-03: SPECIAL IN-PERSON TALK: Keolohilani Lopes Jr
2023-11-03: SPECIAL IN-PERSON TALK: Ieva Daukantas
2023-10-27: Active Learning for Computationally Efficient Distribution of Binary Evolution Simulations, Rocha, et al. 2022 (presented by Mitchell)
2023-10-20: Coupled adversarial learning for fusion classification of hyperspectral and LiDAR data, Lu, et al. 2023 (presented by Sophia)
2023-10-13: Fourier Neural Operator for Parametric Partial Differential Equations, Li, et al. 2020 (presented by Linnea)
2023-10-06: Leveraging Protein Language Models for Accurate Multiple Sequence Alignments, McWhite, et al. 2023 (presented by Will)
2023-09-29: Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture, Assran, et al. 2023 (presented by Moseli)
2023-09-22: MSA Transformer, Rao, et al. 2023 (presented by Rajan)
2023-09-22: Deep Cox Mixtures for Survival Regression, Nagpal, et al. 2021 (presented by Arianna)
2023-09-08: SPECIAL IN-PERSON TALK: John Shepherd, UH Cancer Center, Director of AI Precision Health Institute
2023-08-25: Swin Transformer: Hierarchical Vision Transformer using Shifted Windows, Liu, et al. 2021 (presented by Nick)