Discover and read the best of Twitter Threads about #neuralnetworks

Most recents (24)

Have you ever wondered if your Network has learned malicious abstractions?

We are announcing DORA – the first automatic data-agnostic method to find outlier representations in #NeuralNetworks.

Here are watermark detectors in the pre-trained ResNet18! Image
How DORA works?

DORA unveils the self-explaining capabilities of DNNs by extracting semantic information contained in the synthetic Activation Maximisation Signals (s-AMS) and employing this information further to identify outlier (and potentially infected) representations. Image
Why synthetic signals?

DORA is fast and data-agnostic – you do not have to have the training data on your hands. Moreover, since modern networks are trained on enormous datasets, explaining representations with ImageNet might be misleading! #StarWars Image
Read 12 tweets
"Despite deteriorating health and widening inequalities across the country...there is scope for local areas to make a real difference. Changes in approach, allocation of resources and strengthened partnerships are essential." Michael Marmot @MichaelMarmot…
These are the top 10 cities for work-life balance, according to an analysis — and there isn't a single US city among them…
#WorkLifeBalance, #CitySurvey, #AnalysisResults
Study explores the concept of artificial consciousness in the context of the film 'Being John Malkovich'…
#ArtificialIntelligence, #ArtificialConsciousness, #CinematicSymbols
Read 13 tweets
"Good intentions and accurate data still aren’t enough. You also need to know that you’ve collected the right data and asked the right questions, and these are both much, much harder than the introductory effective altruist material tends to let on."…
Read 13 tweets
“Lots of us have a learning mindset or a growth mindset – it makes the journey more exciting and more fulfilling if you are learning new things, and pushing yourself in new ways.” -- Kweilin Ellingrud @KweilinE…
Controversial impact crater under Greenland's ice is surprisingly ancient | Science | AAAS…
#ImpactCrater, #GreenlandDiscovery, #TimelineEstimates
Read 13 tweets
Following tips may boost model performance across different network structures with up to 5% (mAP or mean Average Precision) without increasing computational costs in any way.

#computervision #pytorch #deeplearning #deeplearningai #100daysofmlcode #neuralnetworks #AI
Visually Coherent Image Mix-up for Object Detection. This has already been proven to be successful in lessening adversarial fears in network classification after testing it on COCO 2017 and PASCAL datasets with YOLOv3 models.
#computervision #pytorch
Read 13 tweets
While #science thought us that we can even cut and paste #genes with #CRISPR technology…even with that we only influence 3% to 5% of #chronicillness. The rest depends on #how you #live your #life!!! So how do we #SelfRegulate our #body?
1. Good #sleep is more important than most think! What happens during sleep? The fluctuation of consciousness…that we call the waking state. But in many wisdom traditions of the world, the waking state is merely a lucid dream that consciousness is having…
Read 41 tweets
I see lots of coders trying to get into #deeplearning (DL) without having math pre-reqs.
Good idea? Bad idea? It can be either ⚖️. Let's talk about that 🧵👇

0. What do we mean by "math skills"? I'm talking: calculus, linear algebra, probability, and statistics.
Let's get something else out of the way: people might accuse you of trying to take a shortcut. But it's perfectly normal (and arguably optimal) to try to see how far you can get with what you already have! The impulse isnt wrong, but it may still be the wrong choice for you.
Without solid math skills, you WILL be limited with how far you can go in DL. This isn't necessarily a problem. People learn how to drive cars all the time without ever intending to build a car of their own. Sometimes driving is enough.
Read 11 tweets

Thread of the very best #YouTube channels and #Twitter accounts to follow for:

#AI/ #ML, #DeepLearning, #neural and all things #datascience

#AI #machinelearning @wiserin10 #datascience #bigdata #artificialintelligence


Analytics India Magazine includes discussions on news, tips for the data ecosystem and a deep dive into #AI/#ML, #deeplearning and #neural networks

#YouTube subscriber count: 38k


Krish Naik is co-founder of and specialises in #machinelearning, #deeplearning, and computer vision. Krish’s #YouTube channel is a deep dive into all things #AI/#ML, perfect for beginners

YouTube subscriber count: 421k
Read 15 tweets
Some of the best resources I came across for intuitively visualizing #NeuralNetworks (how they transform data and classify stuff).
With these resources, Neural Networks will be no longer black boxes for you'll.
A thread 🧵
A playlist by none other than @3blue1brown explaining how forward and backward propagation works with great visualizations as always. You can't miss this ...…
A great article from @ch402 explaining how a neural net transforms the data. He has some other great blogposts too, do check out the complete website…
Read 14 tweets
Daily Bookmarks to GAVNet 07/30/2021…
A process-based approach to understanding and managing triggered seismicity…

#seismicity #ProcessBasedApproach #MultidisciplinaryMethod
A Digital Locksmith Has Decoded Biology’s Molecular Keys…

#NeuralNetworks #ProteinSurfaces #ViralDefenses
Read 8 tweets
Daily Bookmarks to GAVNet 07/16/2021…
How Many Numbers Exist? Infinity Proof Moves Math Closer to an Answer.…

#numbers #mathematics #InfinityProof
Read 8 tweets

23 die in Norway after receiving Pfizer COVID-19 vaccine: officials…

The Epoch Times: Hundreds Sent to Emergency Room After Getting COVID-19 Vaccines.…
Read 181 tweets
Proud to announce our newest graph #research #paper, we introduce directional aggregations, generalize convolutional #neuralnetworks in #graphs and solve bottlenecks in GNNs 1/5
Authors:@Saro2000 @vincentmillions @pl219_Cambridge @williamleif @GabriCorso
By using an underlying vector field F, we can define forward/backward directions and extend differential geometry to include directional smoothing and derivatives. By using different directional fields, the GNN aggregators become powerful enough to generalize CNNs. 2/5
We propose to use the gradient of the low-frequency eigenvector as directional vector field to guide the aggregation. We theoretically prove that it reduce both over-smoothing and over-squashing. 3/5
Read 5 tweets
Please help us welcome our next curator Darryl Takudzwa Griffiths. @BlaqNinja completed his Bachelors Degree in Computer Engineering at DUT, graduated in 2011. Due to struggling to find suitable employment he went on to study multiple certificates from bodies such as Microsoft.
He has certificates in N+ (Computer Networking), A+ (Computer Technician & Technical Support), Certified Ethical Hacking V7 (CEH v7), Offensive Security Certified Professional (OSCP). Sadly even with these, he could not secure his desired post so in 2016 he moved to USA.
Darryl was able to secure a job in a corporation that owns casinos as a system analyst & security architect. Within the same year he embarked on a Masters degree in Robotics & Artificial Intelligence Engineering. In 2017 he resigned from his post and started his own company...
Read 99 tweets
Es un orgullo para la Comunidad de Desarrolladores de Argentina poder acompãnar iniciativas como el #ConnectDay junto a estas empresas @plataforma5la, @distillerylatam, @revistasg y @clarikagroup 💪
¡Hoy es el #ConnectDay! Desde CoDeAr estamos felices de poder acompañar a @wtmriodelaplata, @GDGCordobaARG, @gdgriodelaplata en este día de charlas y de compartir conocimiento en comunidad. Podés sumarte a la transmisión en vivo desde acá:
Comienza la primer charla sobre #DataScience y #Economía, en el contexto de las #transdisciplinas.
Read 118 tweets
PathME unsupervised #multiomics
1) genes space → pathways space
2) for each pathway: collapse pathways from multiple omics to one per patient
3) sparse NMF biclustering

✓compared against SNF and iCluster
✓TCGA x 4
✓source code
✓5-fold CV

Worth noting:
- authors use sNMF consensus from 500 runs (cophenetic correlation + permutation testing to choose # of clusters)
- the autoencoders are denoising
- worth praise is the effort into interpretability (of both features/omics & clinical associations) - see supplement!
Read 9 tweets
A "worrying analysis":

"18 [#deeplearning] algorithms ... presented at top-level research conferences ... Only 7 of them could be reproduced w/ reasonable effort ... 6 of them can often be outperformed w/ comparably simple heuristic methods."


[Updates worth tweeting]

There is much concern about #reproducibility issues and flawed scientific practices in the #ML community in particular & #academia in general.

Both the issues and the concerns are not new.

Isn't it time to put an end to them?
There are several works that have exposed these and similar problems along the years.

👏👏 again to @Maurizio_fd et al. for sharing their paper and addressing #DL algorithms for recommended systems (1st tweet from this thread).

But there is more, unfortunately:
Read 18 tweets

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