可惜我不能去了。。。
Gatsby Unit Quinquennial Symposium
10.30am-6:00pm Monday 22 March 2010
We are delighted to announce the 2010 Gatsby Unit Quinquennial Seminar,
with talks by distinguished researchers in theoretical neuroscience and
machine learning.
The symposium will start at 10:30am on Monday 22nd March in the basement
Lecture Theatre, 33 Queen Square, London WCIN 3BG
All are welcome. Lunch and tea will be provided.
-----------------------------------------------------
REGISTRATION IS REQUIRED : TO REGISTER, PLEASE EMAIL:
asstadmin@gatsby.ucl.ac.uk
before 15 March 2010
-----------------------------------------------------
10:30-11:30 Daniel Wolpert
Department of Engineering, University of Cambridge
Probabilistic models of sensorimotor control and decision making
The effortless ease with which humans move our arms, our
eyes, even our lips when we speak masks the true complexity
of the control processes involved. This is evident when we
try to build machines to perform human control tasks. While
computers can now beat grandmasters at chess, no computer
can yet control a robot to manipulate a chess piece with the
dexterity of a six-year-old child. I will review our recent
work on how the humans learn to make skilled movements
covering probabilistic models of learning, including
Bayesian and structural learning, as well as decision making
and the revision of decisions in the face of uncertainty.
11:30-12:30 Israel Nelken
Dept. of Neurobiology and the ICNC, Hebrew University
The representation of surprise in the auditory system
Neurons in auditory cortex show high sensitivity to rare
sounds, a phenomenon often called stimulus-specific
adaptation (SSA). I will describe our attempts to find out
what do the neurons really respond to, and to what extent
SSA can be understood in terms of the simplest possible
model, consisting of adaptation in narrow frequency
channels. Finally, I will discuss some recent experiments
in which we tested the sensitivity of neurons to features of
the sound sequence that go beyond the rarity of the rare
event, suggesting that neurons in auditory cortex are
sensitive to higher-order regularities of the stimulus
sequence.
12:30-14:30 Lunch and posters
14:30-15:30 John Hertz
Niels Bohr Institute, Copenhagen, and NORDITA, Stockholm
The Inverse Ising Model: Why and How
Ising models form a natural framework for modeling the
distribution of multi-neuron spike patterns: Of all models
that correctly describe the firing rates and pairwise firing
correlations, the Ising model is the one of maximum entropy.
The problem at hand here is an inverse one to that we
usually encounter. Normally, one has a model with given
couplings (Jij) and the task is to compute averages and
correlation functions of the variables of the model. Here
we are given the averages and correlations and the task is
to find the couplings.
In the simplest approach to this problem, one considers only
the measured firing rates and equal-time pairwise firing
correlations and tries to find the Ising model that has
these statistics. In our work we have explored and compared
a number of methods for doing this, using data from a
realistic model network of spiking neurons. Several of
these methods work remarkably well.
This success is tempered, however, by our second set of
findings. Using an information-theoretic measure of the
overall quality of fit, we find that, while the Ising model
is a good description of the distribution of spike patterns
for small populations of neurons (~ 10), it does worse and
worse for larger and larger populations (for reasons that
are not yet understood).
Finally, I will describe some recent work, which extends the
Ising approach to describe non-equal-time firing
correlations.
14:30-15:30 Yair Weiss
School of Computer Science and Engineering,
The Hebrew University of Jerusalem
Learning and inference in low-level vision
Low level vision addresses the issues of labeling and
organizing image pixels according to scene related
properties - such as motion, contrast, depth and
reflectance. I will describe our attempts to understand
low-level vision in humans and machines as optimal inference
given the statistics of the world. In particular, I will
show how message passing algorithms allow us to solve
real-world instances of NP-hard problems and to efficiently
learn energy functions despite an exponential number of
constraints.
16:30-17:00 tea
17:00-18:00 Marty Banks
Visual Space Perception Laboratory, UC Berkeley, USA
Perceptual Bases for Rules of Thumb in Photography
Photographers utilize many rules of thumb for creating
natural-looking pictures. The explanations for these
guidelines are vague and probably incorrect. I will explore
two common photographic rules and argue that they are
understandable from a consideration of the perceptual
mechanisms involved and peoples' viewing habits.
The first rule of thumb concerns the lens focal length
required to produce pictures that are not spatially
distorted. Photography textbooks recommend choosing a focal
length that is ~3/2 the film width. The textbooks state
vaguely that the rule creates a field of view that
corresponds to that of normal vision" (Giancoli, 2000), "the
same perspective as the human eye" (Alesse, 1989), or
"approximates the impression human vision gives" (London et
al., 2005). There are two phenomena related to this
rule. One is perceived spatial distortions in wide-angle
(short focal length) pictures. I will argue that the
perceived distortions are caused by the perceptual
mechanisms people employ to take into account oblique
viewing positions. I will present some demonstrations that
validate this explanation. The second phenomenon is
perceived depth in pictures taken with different focal
lengths. The textbooks argue that pictures taken with short
focal lengths expand perceived depth and those taken with
long focal lengths compress it. I will argue that these
effects are due to a combination of the viewing geometry and
the way people typically look at pictures. I will present
demonstrations to validate this.
The second rule of thumb concerns the camera aperture and
depth-of-field blur. Photography textbooks do not describe a
quantitative rule and treat the magnitude of depth-of-field
blur as arbitrary. I will examine the geometry of apertures,
lenses, and image formation. From that analysis, I will
argue that there is a natural relationship between
depth-of-field blur and the 3D layout of the photographed
scene. I will present demonstrations that human viewers are
sensitive to this relationship. In particular, depicted
scenes are perceived differently depending on the
relationship between blur and 3D layout.
-----------------------------------------------------
REGISTRATION IS REQUIRED : TO REGISTER, PLEASE EMAIL:
asstadmin@gatsby.ucl.ac.uk
before 15 March 2010
