Demo Data from SIGIR 2026 / reviewers in the wild / expert
Pierre-Yves Burgi
dblp:99/468
· DBLP profile ↗
8ranked-venue papers
5as first author
0since 2021 · last 2012
0000-0002-4956-9279ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 7 · 5 first-authorGraphics, computer vision, multimedia, augmented reality and games · 1Human-computer interaction and ubiquitous computing · 1Applied, interdisciplinary, general and emerging computing · 1
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Artificial intelligence
1 paper |
Probabilistic and Bayesian machine learning · 67% 3D vision · 33% | |
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Bioinformatics and computational biology · 100% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Machine learning › Probabilistic and Bayesian machine learning › statistical inference › bayesian inference
bayesian filtering |
0.0 | 1 | 1998 | Visual Motion Estimation and Prediction: A Probabilistic Network Model for Temporal Coherence · ICCV 1998 |
Machine learning › Probabilistic and Bayesian machine learning › statistical inference › bayesian inference › bayesian filtering
kalman filtering |
0.0 | 1 | 1998 | Visual Motion Estimation and Prediction: A Probabilistic Network Model for Temporal Coherence · ICCV 1998 |
Computer vision › 3D vision
motion estimation |
0.0 | 1 | 1998 | Visual Motion Estimation and Prediction: A Probabilistic Network Model for Temporal Coherence · ICCV 1998 |
Bioinformatics and computational biology › computational neuroscience › sensory processing
motion perception |
0.0 | 1 | 1998 | Visual Motion Estimation and Prediction: A Probabilistic Network Model for Temporal Coherence · ICCV 1998 |
Methods — techniques the papers use, named apart from their topics
kalman filtering · 0.0bayesian generalization · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2012 | An Institutional Personal Learning Environment EnablerabstractIn this paper, we first discuss the concept of Personal Learning Environment (PLE) with respect to higher-education institutions and Virtual Learning Environments (VLEs). This discussion rapidly confronts us to the place of the PLE and self-directed learning and/or training inside the institution. We therefore introduce the concept of institutional PLE enabler, which is expected to stimulate students to create and use their own resources and institutional resources and share them with peers during formal and informal learning activities. Next, we describe a proposal for a federated design and implementation of the PLE enabler across multiple institutions. Laurent Moccozet, Omar Benkacem, Pierre-Yves Burgi, Hervé Platteaux, Denis Gillet |
ICALT | 3 |
| 2004 | Motion estimation based on the direction of intensity gradient
Pierre-Yves Burgi |
Image Vis. Comput. | 1 |
| 2000 | Probabilistic Motion Estimation Based on Temporal CoherenceabstractWe develop a theory for the temporal integration of visual motion motivated by psychophysical experiments. The theory proposes that input data are temporally grouped and used to predict and estimate the motion flows in the image sequence. This temporal grouping can be considered a generalization of the data association techniques that engineers use to study motion sequences. Our temporal grouping theory is expressed in terms of the Bayesian generalization of standard Kalman filtering. To implement the theory, we derive a parallel network that shares some properties of cortical networks. Computer simulations of this network demonstrate that our theory qualitatively accounts for psychophysical experiments on motion occlusion and motion outliers. In deriving our theory, we assumed spatial factorizability of the probability distributions and made the approximation of updating the marginal distributions of velocity at each point. This allowed us to perform local computations and simplified our implementation. We argue that these approximations are suitable for the stimuli we are considering (for which spatial coherence effects are negligible). Pierre-Yves Burgi, Alan L. Yuille, Norberto M. Grzywacz |
Neural Comput. | 1 |
| 1998 | Visual Motion Estimation and Prediction: A Probabilistic Network Model for Temporal CoherenceabstractWe develop a theory for the temporal integration of visual motion motivated by psychophysical experiments. The theory proposes that input data are temporally grouped and used to predict and estimate motion flows in the image sequences. Our theory is expressed in terms of the Bayesian generalization of standard Kalman filtering which allows us to solve temporal grouping in conjunction with prediction and estimation. As demonstrated for tracking isolated contours the Bayesian formulation is superior to approaches which use data association as a first stage followed by conventional Kalman filtering. Our computer simulations demonstrate that our theory qualitatively accounts for several psychophysical experiments on motion occlusion and motion outliers. Alan L. Yuille, Pierre-Yves Burgi, Norberto M. Grzywacz |
ICCV | 2 |
| 1998 | Towards A Biophysically Plausible Bidirectional Hebbian RuleabstractAlthough the commonly used quadratic Hebbian-anti-Hebbian rules lead to successful models of plasticity and learning, they are inconsistent with neurophysiology. Other rules, more physiologically plausible, fail to specify the biological mechanism of bidirectionality and the biological mechanism that prevents synapses from changing from excitatory to inhibitory, and vice versa. We developed a synaptic bidirectional Hebbian rule that does not suffer from these problems. This rule was compared with physiological homosynaptic conditions in the hippocampus, with the results indicating the consistency of this rule with long-term potentiation (LTP) and long-term depression (LTD) phenomenologies. The phenomenologies considered included the reversible dynamics of LTP and LTD and the effects of N-methyl-D-aspartate blockers and phosphatase inhibitors. Norberto M. Grzywacz, Pierre-Yves Burgi |
Neural Comput. | 2 |
| 1997 | Possible Roles of Spontaneous Waves and Dendritic Growth for Retinal Receptive Field DevelopmentabstractSeveral models of cortical development postulate that a Hebbian process fed by spontaneous activity amplifies orientation biases occurring randomly in early wiring, to form orientation selectivity. These models are not applicable to the development of retinal orientation selectivity, since they neglect the polarization of the retina's poorly branched early dendritic trees and the wavelike organization of the retina's early noise. There is now evidence that dendritic polarization and spontaneous waves are key in the development of retinal receptive fields. When models of cortical development are modified to take these factors into account, one obtains a model of retinal development in which early dendritic polarization is the seed of orientation selectivity, while the spatial extent of spontaneous waves controls the spatial profile of receptive fields and their tendency to be isotropic. Pierre-Yves Burgi, Norberto M. Grzywacz |
Neural Comput. | 1 |
| 1994 | Model Based on Extracellular Potassium for Spontaneous Synchronous Activity in Developing RetinasabstractWaves of action-potential bursts propagate across the ganglion-cell surface of isolated developing retinas. It has been suggested that the rise of extracellular potassium concentration following a burst of action potentials in a cell may underlie these waves by depolarizing neighbor cells. This suggestion is sensible for developing tissues, since their glial system is immature. We tested whether this extracellular-potassium suggestion is feasible. For this purpose, we built a realistic biophysical model of the ganglion-cell layer of the developing retina. Simulations with this model show that increases of extracellular potassium are sufficiently high (about fourfold) to mediate the waves consistently with experimental physiological and pharmacological data. Even if another mechanism mediates the waves, these simulations indicate that extracellular potassium should significantly modulate the waves' properties. Pierre-Yves Burgi, Norberto M. Grzywacz |
Neural Comput. | 1 |
| 1992 | Analysis and understanding of neuronal structures
Pierre-Yves Burgi |
Neurocomputing | 1 |