A Simple Baseline for Predicting Events with Auto-Regressive Tabular Transformers.
CoRR, 2024
Searching for Efficient Linear Layers over a Continuous Space of Structured Matrices.
CoRR, 2024
Just How Flexible are Neural Networks in Practice?
CoRR, 2024
Searching for Efficient Linear Layers over a Continuous Space of Structured Matrices.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024
From Explanation to Action: An End-to-End Human-in-the-loop Framework for Anomaly Reasoning and Management.
CoRR, 2023
Simplifying Neural Network Training Under Class Imbalance.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
A Performance-Driven Benchmark for Feature Selection in Tabular Deep Learning.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
GOAT: A Global Transformer on Large-scale Graphs.
Proceedings of the International Conference on Machine Learning, 2023
Identifying Interpretable Subspaces in Image Representations.
Proceedings of the International Conference on Machine Learning, 2023
Transfer Learning with Deep Tabular Models.
Proceedings of the Eleventh International Conference on Learning Representations, 2023
From Detection to Action: a Human-in-the-loop Toolkit for Anomaly Reasoning and Management.
Proceedings of the 4th ACM International Conference on AI in Finance, 2023
Adapting Self-Supervised Representations to Multi-Domain Setups.
Proceedings of the 34th British Machine Vision Conference 2023, 2023
BASED-XAI: Breaking Ablation Studies Down for Explainable Artificial Intelligence.
CoRR, 2022
Double-Hashing Algorithm for Frequency Estimation in Data Streams.
CoRR, 2022
Counterfactual Explanations via Latent Space Projection and Interpolation.
CoRR, 2021
MetaBalance: High-Performance Neural Networks for Class-Imbalanced Data.
CoRR, 2021
SAINT: Improved Neural Networks for Tabular Data via Row Attention and Contrastive Pre-Training.
CoRR, 2021
Latent-CF: A Simple Baseline for Reverse Counterfactual Explanations.
CoRR, 2020
DLGNet-Task: An End-to-end Neural Network Framework for Modeling Multi-turn Multi-domain Task-Oriented Dialogue.
CoRR, 2020
Machine Learning for Temporal Data in Finance: Challenges and Opportunities.
CoRR, 2020
Towards Ground Truth Explainability on Tabular Data.
CoRR, 2020
Quantifying Challenges in the Application of Graph Representation Learning.
Proceedings of the 19th IEEE International Conference on Machine Learning and Applications, 2020
Navigating the dynamics of financial embeddings over time.
Proceedings of the ICAIF '20: The First ACM International Conference on AI in Finance, 2020
On the Interpretability and Evaluation of Graph Representation Learning.
CoRR, 2019
DeepTrax: Embedding Graphs of Financial Transactions.
CoRR, 2019
Graph Embeddings at Scale.
CoRR, 2019
Towards Automated Machine Learning: Evaluation and Comparison of AutoML Approaches and Tools.
Proceedings of the 31st IEEE International Conference on Tools with Artificial Intelligence, 2019
DeepTrax: Embedding Graphs of Financial Transactions.
Proceedings of the 18th IEEE International Conference On Machine Learning And Applications, 2019