Hampus Linander

21 papers A* 3Journal 18

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	AXIOM: Learning to Play Games in Minutes with Expanding Object-Centric Models. CoRR Conor Heins, Toon Van de Maele, Alexander Tschantz, Hampus Linander, Dimitrije Markovic, Tommaso Salvatori, Corrado Pezzato, Ozan Çatal, Ran Wei, Magnus T. Koudahl, Marco Perin, Karl J. Friston, Tim Verbelen, Christopher L. Buckley
2025	J	`jnl`	Bayesian Predictive Coding. CoRR Alexander Tschantz, Magnus T. Koudahl, Hampus Linander, Lancelot Da Costa, Conor Heins, Jeff Beck, Christopher L. Buckley
2025	J	`jnl`	Learning Chern Numbers of Topological Insulators with Gauge Equivariant Neural Networks. CoRR Longde Huang, Oleksandr Balabanov, Hampus Linander, Mats Granath, Daniel Persson, Jan E. Gerken
2025	J	`jnl`	PEAR: Equal Area Weather Forecasting on the Sphere. CoRR Hampus Linander, Christoffer Petersson, Daniel Persson, Jan E. Gerken
2025	J	`jnl`	Soft Geometric Inductive Bias for Object Centric Dynamics. CoRR Hampus Linander, Conor Heins, Alexander Tschantz, Marco Perin, Christopher L. Buckley
2024	A*	`conf`	HEAL-SWIN: A Vision Transformer on the Sphere. CVPR Oscar Carlsson, Jan E. Gerken, Hampus Linander, Heiner Spieß, Fredrik Ohlsson, Christoffer Petersson, Daniel Persson
2024	J	`jnl`	Uncertainty quantification in fine-tuned LLMs using LoRA ensembles. CoRR Oleksandr Balabanov, Hampus Linander
2023	A*	`conf`	Bayesian Posterior Approximation With Stochastic Ensembles. CVPR Oleksandr Balabanov, Bernhard Mehlig, Hampus Linander
2023	J	`jnl`	Finite-time Lyapunov exponents of deep neural networks. CoRR L. Storm, Hampus Linander, J. Bec, Kristian Gustavsson, Bernhard Mehlig
2023	J	`jnl`	Geometric deep learning and equivariant neural networks. Artif. Intell. Rev. Jan E. Gerken, Jimmy Aronsson, Oscar Carlsson, Hampus Linander, Fredrik Ohlsson, Christoffer Petersson, Daniel Persson
2023	J	`jnl`	HEAL-SWIN: A Vision Transformer On The Sphere. CoRR Oscar Carlsson, Jan E. Gerken, Hampus Linander, Heiner Spieß, Fredrik Ohlsson, Christoffer Petersson, Daniel Persson
2023	J	`jnl`	Looking at the posterior: accuracy and uncertainty of neural-network predictions. Mach. Learn. Sci. Technol. Hampus Linander, Oleksandr Balabanov, Henry Yang, Bernhard Mehlig
2022	J	`jnl`	Bayesian posterior approximation with stochastic ensembles. CoRR Oleksandr Balabanov, Bernhard Mehlig, Hampus Linander
2022	A*	`conf`	Equivariance versus Augmentation for Spherical Images. ICML Jan E. Gerken, Oscar Carlsson, Hampus Linander, Fredrik Ohlsson, Christoffer Petersson, Daniel Persson
2022	J	`jnl`	Equivariance versus Augmentation for Spherical Images. CoRR Jan E. Gerken, Oscar Carlsson, Hampus Linander, Fredrik Ohlsson, Christoffer Petersson, Daniel Persson
2022	J	`jnl`	Looking at the posterior: on the origin of uncertainty in neural-network classification. CoRR Hampus Linander, Oleksandr Balabanov, Henry Yang, Bernhard Mehlig
2022	J	`jnl`	Real-time semantic segmentation on FPGAs for autonomous vehicles with hls4ml. CoRR Nicolò Ghielmetti, Vladimir Loncar, Maurizio Pierini, Marcel Roed, Sioni Summers, Thea Aarrestad, Christoffer Petersson, Hampus Linander, Jennifer Ngadiuba, Kelvin Lin, Philip C. Harris
2022	J	`jnl`	Real-time semantic segmentation on FPGAs for autonomous vehicles with hls4ml. Mach. Learn. Sci. Technol. Nicolò Ghielmetti, Vladimir Loncar, Maurizio Pierini, Marcel Roed, Sioni Summers, Thea Aarrestad, Christoffer Petersson, Hampus Linander, Jennifer Ngadiuba, Kelvin Lin, Philip C. Harris
2021	J	`jnl`	Fast convolutional neural networks on FPGAs with hls4ml. CoRR Thea Aarrestad, Vladimir Loncar, Maurizio Pierini, Sioni Summers, Jennifer Ngadiuba, Christoffer Petersson, Hampus Linander, Yutaro Iiyama, Giuseppe Di Guglielmo, Javier M. Duarte, Philip C. Harris, Dylan S. Rankin, Sergo Jindariani, Kevin Pedro, Nhan Tran, Mia Liu, Edward Kreinar, Zhenbin Wu, Duc Hoang
2021	J	`jnl`	Fast convolutional neural networks on FPGAs with hls4ml. Mach. Learn. Sci. Technol. Thea Aarrestad, Vladimir Loncar, Nicolò Ghielmetti, Maurizio Pierini, Sioni Summers, Jennifer Ngadiuba, Christoffer Petersson, Hampus Linander, Yutaro Iiyama, Giuseppe Di Guglielmo, Javier M. Duarte, Philip C. Harris, Dylan S. Rankin, Sergo Jindariani, Kevin Pedro, Nhan Tran, Mia Liu, Edward Kreinar, Zhenbin Wu, Duc Hoang
2021	J	`jnl`	Geometric Deep Learning and Equivariant Neural Networks. CoRR Jan E. Gerken, Jimmy Aronsson, Oscar Carlsson, Hampus Linander, Fredrik Ohlsson, Christoffer Petersson, Daniel Persson