Liudmila Prokhorenkova

51 papers A* 18C 2Journal 27Unranked 4

Year	Rank	Type	Title / Venue / Authors
2025	A*	`conf`	Discrete Neural Algorithmic Reasoning. ICML Gleb Rodionov, Liudmila Prokhorenkova
2025	J	`jnl`	Fine-Grained Urban Traffic Forecasting on Metropolis-Scale Road Networks. CoRR Fedor Velikonivtsev, Oleg Platonov, Gleb Bazhenov, Liudmila Prokhorenkova
2025	J	`jnl`	GraphPFN: A Prior-Data Fitted Graph Foundation Model. CoRR Dmitry Eremeev, Oleg Platonov, Gleb Bazhenov, Artem Babenko, Liudmila Prokhorenkova
2025	A*	`conf`	Measuring Diversity: Axioms and Challenges. ICML Mikhail Mironov, Liudmila Prokhorenkova
2025	J	`jnl`	Turning Tabular Foundation Models into Graph Foundation Models. CoRR Dmitry Eremeev, Gleb Bazhenov, Oleg Platonov, Artem Babenko, Liudmila Prokhorenkova
2024	A*	`conf`	Challenges of Generating Structurally Diverse Graphs. NeurIPS Fedor Velikonivtsev, Mikhail Mironov, Liudmila Prokhorenkova
2024	J	`jnl`	Challenges of Generating Structurally Diverse Graphs. CoRR Fedor Velikonivtsev, Mikhail Mironov, Liudmila Prokhorenkova
2024	J	`jnl`	Discrete Neural Algorithmic Reasoning. CoRR Gleb Rodionov, Liudmila Prokhorenkova
2024	J	`jnl`	Evaluating Graph Generative Models with Graph Kernels: What Structural Characteristics Are Captured? Trans. Mach. Learn. Res. Martijn Gösgens, Alexey Tikhonov, Liudmila Prokhorenkova
2024	J	`jnl`	Measuring Diversity: Axioms and Challenges. CoRR Mikhail Mironov, Liudmila Prokhorenkova
2024	—	`conf`	Revisiting Graph Homophily Measures. LoG Mikhail Mironov, Liudmila Prokhorenkova
2024	J	`jnl`	Revisiting Graph Homophily Measures. CoRR Mikhail Mironov, Liudmila Prokhorenkova
2024	J	`jnl`	TabGraphs: A Benchmark and Strong Baselines for Learning on Graphs with Tabular Node Features. CoRR Gleb Bazhenov, Oleg Platonov, Liudmila Prokhorenkova
2023	A*	`conf`	A critical look at the evaluation of GNNs under heterophily: Are we really making progress? ICLR Oleg Platonov, Denis Kuznedelev, Michael Diskin, Artem Babenko, Liudmila Prokhorenkova
2023	J	`jnl`	A critical look at the evaluation of GNNs under heterophily: are we really making progress? CoRR Oleg Platonov, Denis Kuznedelev, Michael Diskin, Artem Babenko, Liudmila Prokhorenkova
2023	A*	`conf`	Characterizing Graph Datasets for Node Classification: Homophily-Heterophily Dichotomy and Beyond. NeurIPS Oleg Platonov, Denis Kuznedelev, Artem Babenko, Liudmila Prokhorenkova
2023	A*	`conf`	Evaluating Robustness and Uncertainty of Graph Models Under Structural Distributional Shifts. NeurIPS Gleb Bazhenov, Denis Kuznedelev, Andrey Malinin, Artem Babenko, Liudmila Prokhorenkova
2023	J	`jnl`	Evaluating Robustness and Uncertainty of Graph Models Under Structural Distributional Shifts. CoRR Gleb Bazhenov, Denis Kuznedelev, Andrey Malinin, Artem Babenko, Liudmila Prokhorenkova
2023	A*	`conf`	Gradient Boosting Performs Gaussian Process Inference. ICLR Aleksei Ustimenko, Artem Beliakov, Liudmila Prokhorenkova
2023	A*	`conf`	Neural Algorithmic Reasoning Without Intermediate Supervision. NeurIPS Gleb Rodionov, Liudmila Prokhorenkova
2023	J	`jnl`	Neural Algorithmic Reasoning Without Intermediate Supervision. CoRR Gleb Rodionov, Liudmila Prokhorenkova
2023	A*	`conf`	Which Tricks are Important for Learning to Rank? ICML Ivan Lyzhin, Aleksei Ustimenko, Andrey Gulin, Liudmila Prokhorenkova
2022	J	`jnl`	Characterizing Graph Datasets for Node Classification: Beyond Homophily-Heterophily Dichotomy. CoRR Oleg Platonov, Denis Kuznedelev, Artem Babenko, Liudmila Prokhorenkova
2022	J	`jnl`	Good Classification Measures and How to Find Them. CoRR Martijn Gösgens, Anton Zhiyanov, Alexey Tikhonov, Liudmila Prokhorenkova
2022	J	`jnl`	Gradient Boosting Performs Low-Rank Gaussian Process Inference. CoRR Aleksei Ustimenko, Artem Beliakov, Liudmila Prokhorenkova
2022	A*	`conf`	Graph-based Nearest Neighbor Search in Hyperbolic Spaces. ICLR Liudmila Prokhorenkova, Dmitry Baranchuk, Nikolay Bogachev, Yury Demidovich, Alexander Kolpakov
2022	J	`jnl`	When Less Is More: Systematic Analysis of Cascade-Based Community Detection. ACM Trans. Knowl. Discov. Data Liudmila Prokhorenkova, Alexey Tikhonov, Nelly Litvak
2022	J	`jnl`	Which Tricks are Important for Learning to Rank? CoRR Ivan Lyzhin, Aleksei Ustimenko, Andrey Gulin, Liudmila Prokhorenkova
2021	A*	`conf`	Boost then Convolve: Gradient Boosting Meets Graph Neural Networks. ICLR Sergei Ivanov, Liudmila Prokhorenkova
2021	J	`jnl`	Boost then Convolve: Gradient Boosting Meets Graph Neural Networks. CoRR Sergei Ivanov, Liudmila Prokhorenkova
2021	A*	`conf`	Good Classification Measures and How to Find Them. NeurIPS Martijn Gösgens, Anton Zhiyanov, Aleksey Tikhonov, Liudmila Prokhorenkova
2021	A*	`conf`	Overlapping Spaces for Compact Graph Representations. NeurIPS Kirill Shevkunov, Liudmila Prokhorenkova
2021	A*	`conf`	SGLB: Stochastic Gradient Langevin Boosting. ICML Aleksei Ustimenko, Liudmila Prokhorenkova
2021	—	`conf`	Shifts: A Dataset of Real Distributional Shift Across Multiple Large-Scale Tasks. NeurIPS Datasets and Benchmarks Andrey Malinin, Neil Band, Yarin Gal, Mark J. F. Gales, Alexander Ganshin, German Chesnokov, Alexey Noskov, Andrey Ploskonosov, Liudmila Prokhorenkova, Ivan Provilkov, Vatsal Raina, Vyas Raina, Denis Roginskiy, Mariya Shmatova, Panagiotis Tigas, Boris Yangel
2021	J	`jnl`	Shifts: A Dataset of Real Distributional Shift Across Multiple Large-Scale Tasks. CoRR Andrey Malinin, Neil Band, Alexander Ganshin, German Chesnokov, Yarin Gal, Mark J. F. Gales, Alexey Noskov, Andrey Ploskonosov, Liudmila Prokhorenkova, Ivan Provilkov, Vatsal Raina, Vyas Raina, Mariya Shmatova, Panos Tigas, Boris Yangel
2021	A*	`conf`	Systematic Analysis of Cluster Similarity Indices: How to Validate Validation Measures. ICML Martijn Gösgens, Alexey Tikhonov, Liudmila Prokhorenkova
2021	A*	`conf`	Uncertainty in Gradient Boosting via Ensembles. ICLR Andrey Malinin, Liudmila Prokhorenkova, Aleksei Ustimenko
2020	—	`conf`	Embedding Words in Non-Vector Space with Unsupervised Graph Learning. EMNLP (1) Max Ryabinin, Sergei Popov, Liudmila Prokhorenkova, Elena Voita
2020	J	`jnl`	Embedding Words in Non-Vector Space with Unsupervised Graph Learning. CoRR Max Ryabinin, Sergei Popov, Liudmila Prokhorenkova, Elena Voita
2020	C	`conf`	Global Graph Curvature. WAW Liudmila Prokhorenkova, Egor Samosvat, Pim van der Hoorn
2020	A*	`conf`	Graph-based Nearest Neighbor Search: From Practice to Theory. ICML Liudmila Prokhorenkova, Aleksandr Shekhovtsov
2020	J	`jnl`	Overlaying Spaces and Practical Applicability of Complex Geometries. CoRR Kirill Shevkunov, Liudmila Prokhorenkova
2020	J	`jnl`	SGLB: Stochastic Gradient Langevin Boosting. CoRR Aleksei Ustimenko, Liudmila Prokhorenkova
2020	A*	`conf`	StochasticRank: Global Optimization of Scale-Free Discrete Functions. ICML Aleksei Ustimenko, Liudmila Prokhorenkova
2020	J	`jnl`	StochasticRank: Global Optimization of Scale-Free Discrete Functions. CoRR Aleksei Ustimenko, Liudmila Prokhorenkova
2020	J	`jnl`	Uncertainty in Gradient Boosting via Ensembles. CoRR Aleksei Ustimenko, Liudmila Prokhorenkova, Andrey Malinin
2020	J	`jnl`	When Less is More: Systematic Analysis of Cascade-based Community Detection. CoRR Liudmila Prokhorenkova, Alexey Tikhonov, Nelly Litvak
2019	—	`conf`	A Statistical Test of Heterogeneous Subgraph Densities to Assess Clusterability. LION Pierre Miasnikof, Liudmila Prokhorenkova, Alexander Y. Shestopaloff, Andrei M. Raigorodskii
2019	J	`jnl`	Graph-based Nearest Neighbor Search: From Practice to Theory. CoRR Liudmila Prokhorenkova
2019	J	`jnl`	Systematic Analysis of Cluster Similarity Indices: Towards Bias-free Cluster Validation. CoRR Martijn Gösgens, Liudmila Prokhorenkova, Alexey Tikhonov
2019	C	`conf`	Using Synthetic Networks for Parameter Tuning in Community Detection. WAW Liudmila Prokhorenkova