Marek Grzes - RankMe

74 papers A* 4A 7B 3C 8Misc 4Journal 32Unranked 13

Year	Rank	Type	Title / Venue / Authors
2025	A*	`conf`	Can Large Language Models Outperform Non-Experts in Poetry Evaluation? A Comparative Study Using the Consensual Assessment Technique. EMNLP Piotr Sawicki, Marek Grzes, Dan Brown, Fabrício Góes
2025	J	`jnl`	Can Large Language Models Outperform Non-Experts in Poetry Evaluation? A Comparative Study Using the Consensual Assessment Technique. CoRR Piotr Sawicki, Marek Grzes, Dan Brown, Fabrício Góes
2024	J	`jnl`	Deconstructing Deep Active Inference: A Contrarian Information Gatherer. Neural Comput. Théophile Champion, Marek Grzes, Lisa Bonheme, Howard Bowman
2024	J	`jnl`	Reframing the Expected Free Energy: Four Formulations and a Unification. CoRR Théophile Champion, Howard Bowman, Dimitrije Markovic, Marek Grzes
2024	J	`jnl`	Structure learning with Temporal Gaussian Mixture for model-based Reinforcement Learning. CoRR Théophile Champion, Marek Grzes, Howard Bowman
2023	J	`jnl`	Be More Active! Understanding the Differences Between Mean and Sampled Representations of Variational Autoencoders. J. Mach. Learn. Res. Lisa Bonheme, Marek Grzes
2023	C	`conf`	Bits of Grass: Does GPT already know how to write like Whitman? ICCC Piotr Sawicki, Marek Grzes, Fabrício Góes, Dan Brown, Max Peeperkorn, Aisha Khatun
2023	J	`jnl`	Bits of Grass: Does GPT already know how to write like Whitman? CoRR Piotr Sawicki, Marek Grzes, Fabrício Góes, Dan Brown, Max Peeperkorn, Aisha Khatun
2023	J	`jnl`	Deconstructing deep active inference. CoRR Théophile Champion, Marek Grzes, Lisa Bonheme, Howard Bowman
2023	J	`jnl`	How good are variational autoencoders at transfer learning? CoRR Lisa Bonheme, Marek Grzes
2023	C	`conf`	Is GPT-4 Good Enough to Evaluate Jokes? ICCC Fabrício Góes, Piotr Sawicki, Marek Grzes, Marco Volpe, Dan Brown
2023	C	`conf`	On the power of special-purpose GPT models to create and evaluate new poetry in old styles. ICCC Piotr Sawicki, Marek Grzes, Fabrício Góes, Anna Jordanous, Dan Brown, Simona Paraskevopoulou, Max Peeperkorn, Aisha Khatun
2023	C	`conf`	Posterior Collapse in Variational Gradient Origin Networks. ICMLA Peter Clapham, Marek Grzes
2023	C	`conf`	Pushing GPT's Creativity to Its Limits: Alternative Uses and Torrance Tests. ICCC Fabrício Góes, Piotr Sawicki, Marek Grzes, Marco Volpe, Jacob Watson
2023	—	`conf`	The Polarised Regime of identifiable Variational Autoencoders. Tiny Papers @ ICLR Lisa Bonheme, Marek Grzes
2022	J	`jnl`	Branching Time Active Inference with Bayesian Filtering. Neural Comput. Théophile Champion, Marek Grzes, Howard Bowman
2022	J	`jnl`	Branching Time Active Inference: The theory and its generality. Neural Networks Théophile Champion, Lancelot Da Costa, Howard Bowman, Marek Grzes
2022	J	`jnl`	Branching time active inference: Empirical study and complexity class analysis. Neural Networks Théophile Champion, Howard Bowman, Marek Grzes
2022	J	`jnl`	Crowd Score: A Method for the Evaluation of Jokes using Large Language Model AI Voters as Judges. CoRR Fabrício Góes, Zisen Zhou, Piotr Sawicki, Marek Grzes, Daniel G. Brown
2022	J	`jnl`	FONDUE: an algorithm to find the optimal dimensionality of the latent representations of variational autoencoders. CoRR Lisa Bonheme, Marek Grzes
2022	J	`jnl`	How do Variational Autoencoders Learn? Insights from Representational Similarity. CoRR Lisa Bonheme, Marek Grzes
2022	J	`jnl`	Multi-Modal and Multi-Factor Branching Time Active Inference. CoRR Théophile Champion, Marek Grzes, Howard Bowman
2022	C	`conf`	Training GPT-2 to represent two Romantic-era authors: challenges, evaluations and pitfalls. ICCC Piotr Sawicki, Marek Grzes, Anna Jordanous, Dan Brown, Max Peeperkorn
2021	J	`jnl`	Be More Active! Understanding the Differences between Mean and Sampled Representations of Variational Autoencoders. CoRR Lisa Bonheme, Marek Grzes
2021	J	`jnl`	Branching Time Active Inference with Bayesian Filtering. CoRR Théophile Champion, Marek Grzes, Howard Bowman
2021	J	`jnl`	Branching Time Active Inference: empirical study and complexity class analysis. CoRR Théophile Champion, Howard Bowman, Marek Grzes
2021	J	`jnl`	Branching Time Active Inference: the theory and its generality. CoRR Théophile Champion, Lancelot Da Costa, Howard Bowman, Marek Grzes
2021	J	`jnl`	Realising Active Inference in Variational Message Passing: the Outcome-blind Certainty Seeker. CoRR Théophile Champion, Marek Grzes, Howard Bowman
2021	J	`jnl`	Realizing Active Inference in Variational Message Passing: The Outcome-Blind Certainty Seeker. Neural Comput. Théophile Champion, Marek Grzes, Howard Bowman
2020	—	`conf`	SESAM at SemEval-2020 Task 8: Investigating the Relationship between Image and Text in Sentiment Analysis of Memes. SemEval@COLING Lisa Bonheme, Marek Grzes
2019	B	`conf`	Comparing Explanations between Random Forests and Artificial Neural Networks. SMC Lee Harris, Marek Grzes
2019	—	`conf`	Self-adaptive artificial intelligence. SEAMS@ICSE Rogério de Lemos, Marek Grzes
2018	A*	`conf`	Improving Language Modelling with Noise Contrastive Estimation. AAAI Farhana Ferdousi Liza, Marek Grzes
2018	J	`jnl`	Reinforcement Learning using Augmented Neural Networks. CoRR Jack Shannon, Marek Grzes
2017	J	`jnl`	Improving Language Modelling with Noise-contrastive estimation. CoRR Farhana Ferdousi Liza, Marek Grzes
2017	A	`conf`	Reward Shaping in Episodic Reinforcement Learning. AAMAS Marek Grzes
2016	—	`conf`	A Spectral Method that Worked Well in the SPiCe'16 Competition. ICGI Farhana Ferdousi Liza, Marek Grzes
2016	—	`conf`	An Improved Crowdsourcing Based Evaluation Technique for Word Embedding Methods. RepEval@ACL Farhana Ferdousi Liza, Marek Grzes
2016	Misc	`conf`	Estimating the Accuracy of Spectral Learning for HMMs. AIMSA Farhana Ferdousi Liza, Marek Grzes
2015	J	`jnl`	Energy Efficient Execution of POMDP Policies. IEEE Trans. Cybern. Marek Grzes, Pascal Poupart, Xiao Yang, Jesse Hoey
2015	A	`conf`	Incremental Policy Iteration with Guaranteed Escape from Local Optima in POMDP Planning. AAMAS Marek Grzes, Pascal Poupart
2015	J	`jnl`	The 2014 International Planning Competition: Progress and Trends. AI Mag. Mauro Vallati, Lukás Chrpa, Marek Grzes, Thomas Leo McCluskey, Mark Roberts, Scott Sanner
2014	J	`jnl`	Multi-test decision tree and its application to microarray data classification. Artif. Intell. Medicine Marcin Czajkowski, Marek Grzes, Marek Kretowski
2014	A	`conf`	POMDP planning and execution in an augmented space. AAMAS Marek Grzes, Pascal Poupart
2014	J	`jnl`	Relational approach to knowledge engineering for POMDP-based assistance systems as a translation of a psychological model. Int. J. Approx. Reason. Marek Grzes, Jesse Hoey, Shehroz S. Khan, Alex Mihailidis, Stephen Czarnuch, Daniel Jackson, Andrew Monk
2013	—	`conf`	Controller Compilation and Compression for Resource Constrained Applications. ADT Marek Grzes, Pascal Poupart, Jesse Hoey
2013	A*	`conf`	Isomorph-Free Branch and Bound Search for Finite State Controllers. IJCAI Marek Grzes, Pascal Poupart, Jesse Hoey
2013	B	`conf`	On the convergence of techniques that improve value iteration. IJCNN Marek Grzes, Jesse Hoey
2012	—	`ed.`	Adaptive and Learning Agents - International Workshop, ALA 2011, Held at AAMAS 2011, Taipei, Taiwan, May 2, 2011, Revised Selected Papers ALA Peter Vrancx, Matthew Knudson, Marek Grzes
2012	A	`conf`	Analysis of methods for solving MDPs. AAMAS Marek Grzes, Jesse Hoey
2012	J	`jnl`	Relational Approach to Knowledge Engineering for POMDP-based Assistance Systems as a Translation of a Psychological Model CoRR Marek Grzes, Jesse Hoey, Shehroz S. Khan, Alex Mihailidis, Stephen Czarnuch, Daniel Jackson, Andrew Monk
2011	J	`jnl`	An Empirical Study of Potential-Based Reward Shaping and Advice in Complex, Multi-Agent Systems. Adv. Complex Syst. Sam Devlin, Daniel Kudenko, Marek Grzes
2011	A*	`conf`	Distributed Control of Situated Assistance in Large Domains with Many Tasks. ICAPS Jesse Hoey, Marek Grzes
2011	A	`conf`	Efficient planning in R-max. AAMAS Marek Grzes, Jesse Hoey
2011	—	`conf`	Multi-Test Decision Trees for Gene Expression Data Analysis. SIIS Marcin Czajkowski, Marek Grzes, Marek Kretowski
2011	A	`conf`	Multi-agent, reward shaping for RoboCup KeepAway. AAMAS Sam Devlin, Marek Grzes, Daniel Kudenko
2010	—	`—`	Improving exploration in reinforcement learning through domain knowledge and parameter analysis. Marek Grzes
2010	J	`jnl`	Online learning of shaping rewards in reinforcement learning. Neural Networks Marek Grzes, Daniel Kudenko
2010	A	`conf`	PAC-MDP learning with knowledge-based admissible models. AAMAS Marek Grzes, Daniel Kudenko
2009	—	`conf`	Improving Optimistic Exploration in Model-Free Reinforcement Learning. ICANNGA Marek Grzes, Daniel Kudenko
2009	—	`conf`	Knowledge-Based Reinforcement Learning for Data Mining. ADMI Daniel Kudenko, Marek Grzes
2009	—	`conf`	Reinforcement Learning in RoboCup KeepAway with Partial Observability. IAT Sam Devlin, Marek Grzes, Daniel Kudenko
2009	J	`jnl`	Reinforcement Learning with Reward Shaping and Mixed Resolution Function Approximation. Int. J. Agent Technol. Syst. Marek Grzes, Daniel Kudenko
2009	C	`conf`	Theoretical and Empirical Analysis of Reward Shaping in Reinforcement Learning. ICMLA Marek Grzes, Daniel Kudenko
2008	Misc	`conf`	An Empirical Analysis of the Impact of Prioritised Sweeping on the DynaQ's Performance. ICAISC Marek Grzes, Daniel Kudenko
2008	—	`conf`	Multigrid Reinforcement Learning with Reward Shaping. ICANN (1) Marek Grzes, Daniel Kudenko
2008	Misc	`conf`	Robustness Analysis of SARSA(lambda): Different Models of Reward and Initialisation. AIMSA Marek Grzes, Daniel Kudenko
2007	—	`conf`	Evolutionary Induction of Decision Trees for Misclassification Cost Minimization. ICANNGA (1) Marek Kretowski, Marek Grzes
2007	J	`jnl`	Evolutionary Induction of Mixed Decision Trees. Int. J. Data Warehous. Min. Marek Kretowski, Marek Grzes
2006	C	`conf`	Evolutionary Induction of Cost-Sensitive Decision Trees. ISMIS Marek Kretowski, Marek Grzes
2006	Misc	`conf`	Evolutionary Learning of Linear Trees with Embedded Feature Selection. ICAISC Marek Kretowski, Marek Grzes
2006	B	`conf`	Mixed Decision Trees: An Evolutionary Approach. DaWaK Marek Kretowski, Marek Grzes
2005	—	`conf`	Global Induction of Oblique Decision Trees: An Evolutionary Approach. Intelligent Information Systems Marek Kretowski, Marek Grzes
2005	—	`ch.`	Global learning of decision trees by an evolutionary algorithm. Information Processing and Security Systems Marek Kretowski, Marek Grzes