Kenji Kawaguchi

Zhongqiang Zhang

CoRR, 2024

Towards 3D Molecule-Text Interpretation in Language Models.

[BibT_eX]

[DOI]

CoRR, 2024

The Stronger the Diffusion Model, the Easier the Backdoor: Data Poisoning to Induce Copyright Breaches Without Adjusting Finetuning Pipeline.

[BibT_eX]

[DOI]

CoRR, 2024

Simple Hierarchical Planning with Diffusion.

[BibT_eX]

[DOI]

CoRR, 2024

Can AI Be as Creative as Humans?

[BibT_eX]

[DOI]

CoRR, 2024

Towards Continual Learning Desiderata via HSIC-Bottleneck Orthogonalization and Equiangular Embedding.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Combined scaling for zero-shot transfer learning.

[BibT_eX]

[DOI]

Neurocomputing, October, 2023

Hutchinson Trace Estimation for High-Dimensional and High-Order Physics-Informed Neural Networks.

[BibT_eX]

[DOI]

Zekun Shi

CoRR, 2023

Prompt Optimization via Adversarial In-Context Learning.

[BibT_eX]

[DOI]

CoRR, 2023

Learning Unorthogonalized Matrices for Rotation Estimation.

[BibT_eX]

[DOI]

CoRR, 2023

Probabilistic Copyright Protection Can Fail for Text-to-Image Generative Models.

[BibT_eX]

[DOI]

Xiang Li

Qianli Shen

CoRR, 2023

Bias-Variance Trade-off in Physics-Informed Neural Networks with Randomized Smoothing for High-Dimensional PDEs.

[BibT_eX]

[DOI]

Zhouhao Yang

Yezhen Wang

CoRR, 2023

Investigating Copyright Issues of Diffusion Models under Practical Scenarios.

[BibT_eX]

[DOI]

CoRR, 2023

ChOiRe: Characterizing and Predicting Human Opinions with Chain of Opinion Reasoning.

[BibT_eX]

[DOI]

CoRR, 2023

Rethinking Tokenizer and Decoder in Masked Graph Modeling for Molecules.

[BibT_eX]

[DOI]

CoRR, 2023

AttributionLab: Faithfulness of Feature Attribution Under Controllable Environments.

[BibT_eX]

[DOI]

CoRR, 2023

Self-Supervised Dataset Distillation for Transfer Learning.

[BibT_eX]

[DOI]

CoRR, 2023

A Dual-Perspective Approach to Evaluating Feature Attribution Methods.

[BibT_eX]

[DOI]

CoRR, 2023

Tackling the Curse of Dimensionality with Physics-Informed Neural Networks.

[BibT_eX]

[DOI]

Khemraj Shukla

Ponnuthurai Nagaratnam Suganthan

CoRR, 2023

IF2Net: Innately Forgetting-Free Networks for Continual Learning.

[BibT_eX]

[DOI]

CoRR, 2023

Fast Diffusion Model.

[BibT_eX]

[DOI]

CoRR, 2023

Automatic Model Selection with Large Language Models for Reasoning.

[BibT_eX]

[DOI]

CoRR, 2023

Decomposition Enhances Reasoning via Self-Evaluation Guided Decoding.

[BibT_eX]

[DOI]

CoRR, 2023

Last-Layer Fairness Fine-tuning is Simple and Effective for Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2023

An Information-Theoretic Perspective on Variance-Invariance-Covariance Regularization.

[BibT_eX]

[DOI]

CoRR, 2023

MixupE: Understanding and improving Mixup from directional derivative perspective.

[BibT_eX]

[DOI]

Proceedings of the Uncertainty in Artificial Intelligence, 2023

Self-Evaluation Guided Beam Search for Reasoning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

An Information Theory Perspective on Variance-Invariance-Covariance Regularization.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

PICProp: Physics-Informed Confidence Propagation for Uncertainty Quantification.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Rethinking Tokenizer and Decoder in Masked Graph Modeling for Molecules.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Knowledge-Augmented Reasoning Distillation for Small Language Models in Knowledge-Intensive Tasks.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Sketch-Based Anomaly Detection in Streaming Graphs.

[BibT_eX]

[DOI]

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Scalable Set Encoding with Universal Mini-Batch Consistency and Unbiased Full Set Gradient Approximation.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

Discrete Key-Value Bottleneck.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

Auxiliary Learning as an Asymmetric Bargaining Game.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

GFlowOut: Dropout with Generative Flow Networks.

[BibT_eX]

[DOI]

Dianbo Liu

Moksh Jain

Bonaventure F. P. Dossou

Chris Chinenye Emezue

Proceedings of the International Conference on Machine Learning, 2023

How Does Information Bottleneck Help Deep Learning?

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

D4FT: A Deep Learning Approach to Kohn-Sham Density Functional Theory.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Self-Supervised Set Representation Learning for Unsupervised Meta-Learning.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Self-Distillation for Further Pre-training of Transformers.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Simplicial Embeddings in Self-Supervised Learning and Downstream Classification.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Automatic Model Selection with Large Language Models for Reasoning.

[BibT_eX]

[DOI]

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

MolCA: Molecular Graph-Language Modeling with Cross-Modal Projector and Uni-Modal Adapter.

[BibT_eX]

[DOI]

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

Understanding and Improving Neural Active Learning on Heteroskedastic Distributions.

[BibT_eX]

[DOI]

Proceedings of the ECAI 2023 - 26th European Conference on Artificial Intelligence, September 30 - October 4, 2023, Kraków, Poland, 2023

Adaptive Discrete Communication Bottlenecks with Dynamic Vector Quantization for Heterogeneous Representational Coarseness.

[BibT_eX]

[DOI]

Dianbo Liu

Alex Lamb

Xu Ji

Pascal Tikeng Notsawo Jr.

Michael Mozer

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

When Do Extended Physics-Informed Neural Networks (XPINNs) Improve Generalization?

[BibT_eX]

[DOI]

SIAM J. Sci. Comput., 2022

Interpolation consistency training for semi-supervised learning.

[BibT_eX]

[DOI]

Neural Networks, 2022

Interpolated Adversarial Training: Achieving robust neural networks without sacrificing too much accuracy.

[BibT_eX]

[DOI]

Neural Networks, 2022

Understanding Dynamics of Nonlinear Representation Learning and Its Application.

[BibT_eX]

[DOI]

Linjun Zhang

Zhun Deng

Neural Comput., 2022

Meta-learning PINN loss functions.

[BibT_eX]

[DOI]

Apostolos F. Psaros

J. Comput. Phys., 2022

Deep Kronecker neural networks: A general framework for neural networks with adaptive activation functions.

[BibT_eX]

[DOI]

Yeonjong Shin

Neurocomputing, 2022

MixupE: Understanding and Improving Mixup from Directional Derivative Perspective.

[BibT_eX]

[DOI]

CoRR, 2022

Augmented Physics-Informed Neural Networks (APINNs): A gating network-based soft domain decomposition methodology.

[BibT_eX]

[DOI]

CoRR, 2022

Neural Active Learning on Heteroskedastic Distributions.

[BibT_eX]

[DOI]

CoRR, 2022

Discrete Factorial Representations as an Abstraction for Goal Conditioned Reinforcement Learning.

[BibT_eX]

[DOI]

Remi Tachet des Combes

CoRR, 2022

Simplicial Embeddings in Self-Supervised Learning and Downstream Classification.

[BibT_eX]

[DOI]

CoRR, 2022

Adaptive Discrete Communication Bottlenecks with Dynamic Vector Quantization.

[BibT_eX]

[DOI]

CoRR, 2022

ExpertNet: A Symbiosis of Classification and Clustering.

[BibT_eX]

[DOI]

Shivin Srivastava

Vaibhav Rajan

CoRR, 2022

Training Free Graph Neural Networks for Graph Matching.

[BibT_eX]

[DOI]

CoRR, 2022

MemStream: Memory-Based Streaming Anomaly Detection.

[BibT_eX]

[DOI]

Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

MGNNI: Multiscale Graph Neural Networks with Implicit Layers.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Set-based Meta-Interpolation for Few-Task Meta-Learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Discrete Compositional Representations as an Abstraction for Goal Conditioned Reinforcement Learning.

[BibT_eX]

[DOI]

Remi Tachet des Combes

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

When and How Mixup Improves Calibration.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

Multi-Task Learning as a Bargaining Game.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

Robustness Implies Generalization via Data-Dependent Generalization Bounds.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

2021

MemStream: Memory-Based Anomaly Detection in Multi-Aspect Streams with Concept Drift.

[BibT_eX]

[DOI]

CoRR, 2021

CAC: A Clustering Based Framework for Classification.

[BibT_eX]

[DOI]

CoRR, 2021

Discrete-Valued Neural Communication.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

EIGNN: Efficient Infinite-Depth Graph Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Understanding End-to-End Model-Based Reinforcement Learning Methods as Implicit Parameterization.

[BibT_eX]

[DOI]

Clement Gehring

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Adversarial Training Helps Transfer Learning via Better Representations.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Noether Networks: meta-learning useful conserved quantities.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Tailoring: encoding inductive biases by optimizing unsupervised objectives at prediction time.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Optimization of Graph Neural Networks: Implicit Acceleration by Skip Connections and More Depth.

[BibT_eX]

[DOI]

Proceedings of the 38th International Conference on Machine Learning, 2021

Towards Domain-Agnostic Contrastive Learning.

[BibT_eX]

[DOI]

Proceedings of the 38th International Conference on Machine Learning, 2021

How Does Mixup Help With Robustness and Generalization?

[BibT_eX]

[DOI]

Proceedings of the 9th International Conference on Learning Representations, 2021

On the Theory of Implicit Deep Learning: Global Convergence with Implicit Layers.

[BibT_eX]

[DOI]

Proceedings of the 9th International Conference on Learning Representations, 2021

How Shrinking Gradient Noise Helps the Performance of Neural Networks.

[BibT_eX]

[DOI]

Zhun Deng

Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021

GraphMix: Improved Training of GNNs for Semi-Supervised Learning.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

A Recipe for Global Convergence Guarantee in Deep Neural Networks.

[BibT_eX]

[DOI]

Qingyun Sun

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Adaptive activation functions accelerate convergence in deep and physics-informed neural networks.

[BibT_eX]

[DOI]

J. Comput. Phys., 2020

Towards Domain-Agnostic Contrastive Learning.

[BibT_eX]

[DOI]

CoRR, 2020

Tailoring: encoding inductive biases by optimizing unsupervised objectives at prediction time.

[BibT_eX]

[DOI]

Ferran Alet

Tomás Lozano-Pérez

CoRR, 2020

Ordered SGD: A New Stochastic Optimization Framework for Empirical Risk Minimization.

[BibT_eX]

[DOI]

Haihao Lu

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Elimination of All Bad Local Minima in Deep Learning.

[BibT_eX]

[DOI]

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Depth with nonlinearity creates no bad local minima in ResNets.

[BibT_eX]

[DOI]

Neural Networks, 2019

Every Local Minimum Value Is the Global Minimum Value of Induced Model in Nonconvex Machine Learning.

[BibT_eX]

[DOI]

Neural Comput., 2019

Effect of Depth and Width on Local Minima in Deep Learning.

[BibT_eX]

[DOI]

Neural Comput., 2019

Locally adaptive activation functions with slope recovery term for deep and physics-informed neural networks.

[BibT_eX]

[DOI]

George E. Karniadakis

CoRR, 2019

A Stochastic First-Order Method for Ordered Empirical Risk Minimization.

[BibT_eX]

[DOI]

Haihao Lu

CoRR, 2019

Every Local Minimum is a Global Minimum of an Induced Model.

[BibT_eX]

[DOI]

CoRR, 2019

Eliminating all bad Local Minima from Loss Landscapes without even adding an Extra Unit.

[BibT_eX]

[DOI]

Jascha Sohl-Dickstein

CoRR, 2019

Gradient Descent Finds Global Minima for Generalizable Deep Neural Networks of Practical Sizes.

[BibT_eX]

[DOI]

Proceedings of the 57th Annual Allerton Conference on Communication, 2019

2018

Generalization in Machine Learning via Analytical Learning Theory.

[BibT_eX]

[DOI]

CoRR, 2018

Theory of Deep Learning III: explaining the non-overfitting puzzle.

[BibT_eX]

[DOI]

Hrushikesh N. Mhaskar

CoRR, 2018

Deep Semi-Random Features for Nonlinear Function Approximation.

[BibT_eX]

[DOI]

Bo Xie

Le Song

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017

Generalization in Deep Learning.

[BibT_eX]

[DOI]

CoRR, 2017

Depth Creates No Bad Local Minima.

[BibT_eX]

[DOI]

Haihao Lu

CoRR, 2017

2016

Global Continuous Optimization with Error Bound and Fast Convergence.

[BibT_eX]

[DOI]

Yu Maruyama

Xiaoyu Zheng

J. Artif. Intell. Res., 2016

Streaming Normalization: Towards Simpler and More Biologically-plausible Normalizations for Online and Recurrent Learning.

[BibT_eX]

[DOI]

Qianli Liao

Tomaso A. Poggio

CoRR, 2016

Deep Learning without Poor Local Minima.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Bounded Optimal Exploration in MDP.

[BibT_eX]

[DOI]

Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015

Application of Bayesian nonparametric models to the uncertainty and sensitivity analysis of source term in a BWR severe accident.

[BibT_eX]

[DOI]

Reliab. Eng. Syst. Saf., 2015

Bayesian Optimization with Exponential Convergence.

[BibT_eX]

[DOI]

Tomás Lozano-Pérez

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

2013

A Greedy Approximation of Bayesian Reinforcement Learning with Probably Optimistic Transition Model

[BibT_eX]

[DOI]

Mauricio Araya-López

CoRR, 2013

Prior-Free Exploration Bonus for and beyond Near Bayes-Optimal Behavior.

[BibT_eX]

[DOI]