Poornima Ramesh (@pramesh95) 's Twitter Profile
Poornima Ramesh

@pramesh95

Data Scientist at IDinsight

ID: 1083636024

linkhttp://poornimaramesh.github.io calendar_today12-01-2013 17:45:05

38 Tweet

94 Followers

58 Following

Machine Learning in Science (@mackelab) 's Twitter Profile Photo

The brain can encode information in the phase of oscillations. Want to find out how recurrent neural networks, popular models of neural processing, do this? Watch a short recorded talk by Matthijs Pals at #nmc22 reddit.com/r/neuromatch/c… -Co-supervised by Omri Barak

Stefanie Liebe (@steliebe) 's Twitter Profile Photo

I don’t remember what life was like before starting this project years ago, but somehow our brains track the order of events well. How? See our paper on spike phase coding in human MTL and RNNs with J.Niediek Matthijs Pals Machine Learning in Science @humansingleunit biorxiv.org/content/10.110… 1/5

I don’t remember what life was like before starting this project years ago, but somehow our brains track the order of events well. How? See our paper on spike phase coding in human MTL and RNNs with J.Niediek <a href="/matthijs_pals/">Matthijs Pals</a> <a href="/mackelab/">Machine Learning in Science</a> @humansingleunit biorxiv.org/content/10.110… 1/5
Jakob Macke (@jakhmack) 's Twitter Profile Photo

Preprint: Stefanie Liebe J Niediek et al @humansingleunit recorded 100s of single units in humans, found funky firing during memory tasks. Matthijs Pals task-trained RNNs which exhibit similar patterns and point to potential mechanisms. (Also, cameos by the 👸 and Stable Diffusion.)

IDinsight (@idinsight) 's Twitter Profile Photo

(2/2) Bring your skills to the test and try to classify crops across agricultural fields in Northern India! Know someone who’d be interested in the challenge? Tag them in the comments! 🗓Competition closes on October, 31. bit.ly/3DMea2a

Tim Vogels (@tpvogels) 's Twitter Profile Photo

Dear #neurotwitter, we dropped this onto bioRxiv Neuroscience for your perusal. It's an unusual piece from my lab & I really, really enjoyed working on it with @chc1987. Here it is: Metabolically spikes serve neuronal energy homeostasis (and protect neurons). doi.org/10.1101/2022.1…

Dear #neurotwitter, we dropped this onto <a href="/biorxiv_neursci/">bioRxiv Neuroscience</a> for your perusal. It's an unusual piece from my lab &amp; I really, really enjoyed working on it with @chc1987. Here it is: Metabolically spikes serve neuronal energy homeostasis (and protect neurons). doi.org/10.1101/2022.1…
Machine Learning in Science (@mackelab) 's Twitter Profile Photo

Can circuits generate functional, energy-efficient, and temperature-robust neural activity with widely disparate sets of membrane and synaptic conductances? Check it out in our latest work, now out PNASNews pnas.org/doi/10.1073/pn…! By Michael Deistler Jakob Macke @ppjgoncalves

Jakob Macke (@jakhmack) 's Twitter Profile Photo

Now in final form, many congrats to Michael Deistler , and to @ppjgoncalves for his first last-author paper! This paper benefited greatly from peer review: it was first rejected post peer review from @elife — sure that hurt but the reasons were understandable and highly constructive.

sbi developers (@sbi_devs) 's Twitter Profile Photo

📢 We just released a new sbi version with many improvements and several new features: a SNPE-method that avoids “leakage”, expected coverage tests, and embedding networks that allow iid data for SNPE 🧵 1/6

ML⇌Science Colaboratory (@mlcolab) 's Twitter Profile Photo

Our preprint "Spatiotemporal modeling of European paleoclimate using doubly sparse Gaussian processes" is on arXiv.org! This is one of the outcomes of a cooperation we (Seth Axen 🪓 @alpiges 🐘 Álvaro Tejero-Cantero @[email protected]) are currently running with @sommer_geo and Nils Weitzel! arxiv.org/abs/2211.08160

Our preprint "Spatiotemporal modeling of European paleoclimate using doubly sparse Gaussian processes" is on <a href="/arxiv/">arXiv.org</a>! This is one of the outcomes of a cooperation we (<a href="/sethaxen/">Seth Axen 🪓</a> @alpiges <a href="/alvorithm/">🐘 Álvaro Tejero-Cantero @alvaro@bayes.club</a>) are currently running with @sommer_geo and Nils Weitzel!

arxiv.org/abs/2211.08160
Jonas Beck (@__jnsbck__) 's Twitter Profile Photo

Stoked to share my first #NeurIPS2022 paper. "Efficient Identification of informative features in SBI" arxiv.org/abs/2210.11915 w. Michael Deistler, @yvesbernaerts, Jakob Macke, @CellTypist ML4Science We use NLE to efficiently identify how features constrain posteriors in SBI. (1/8)

Stoked to share my first #NeurIPS2022 paper.

"Efficient Identification of informative features in SBI"

arxiv.org/abs/2210.11915

w. <a href="/deismic_/">Michael Deistler</a>, @yvesbernaerts, <a href="/jakhmack/">Jakob Macke</a>, @CellTypist
<a href="/ml4science/">ML4Science</a>

We use NLE to efficiently identify how features constrain posteriors in SBI. (1/8)
sbi developers (@sbi_devs) 's Twitter Profile Photo

🔔It’s Neural Ratio Estimation (NRE) time🎄! We are happy to announce that two new NRE methods have been contributed to the SBI toolkit: Many thanks to Benjamin Kurt Miller for contributing Contrastive NRE, and to Arnaud Delaunoy for contributing Balanced NRE. 🕯️/ 4

Jakob Macke (@jakhmack) 's Twitter Profile Photo

Just quick: Hugely excited to be given the chance to work on a new project (more details soon) on building network models of large-scale neural computations. Many thanks to the fantastic Machine Learning in Science ML4Science, Srini Turaga + Janne Lappalainen for the joint work on which this builds!

Tim Vogels (@tpvogels) 's Twitter Profile Photo

Over the years my lab has been working on #meta_learning #plasticity rules in #spiking networks. Here's progress report on how far we can get using a twist on simulation based inference (fSBI), presented at NeurIPS Conference (#405) w/ Basile Confavreux, Poornima Ramesh @ppjgoncalves & Jakob Macke.

IDinsight (@idinsight) 's Twitter Profile Photo

🥁 As we kick off 2024, we are sharing our 5 most-read #blogs from last year! 🥁 NUMBER 5️⃣ ~ Satellite imagery combined with AI can help make important predictions for #globaldev practitioners, for example, of forest cover or population census information. #MOSAIKS, created by

🥁 As we kick off 2024, we are sharing our 5 most-read #blogs from last year! 🥁

NUMBER 5️⃣ ~ Satellite imagery combined with AI can help make important predictions for #globaldev practitioners, for example, of forest cover or population census information. #MOSAIKS, created by
IDinsight (@idinsight) 's Twitter Profile Photo

#Top5blogs NUMBER 4️⃣: You’ve planned your research design, assigned schools to treatment and control groups, conducted data collection, and are ready to dive in and clean your data set -- only to realize your research design HASN’T been followed! What do you do? Start over? Or

#Top5blogs NUMBER 4️⃣: You’ve planned your research design, assigned schools to treatment and control groups, conducted data collection, and are ready to dive in and clean your data set -- only to realize your research design HASN’T been followed! What do you do? Start over? Or
The Agency Fund (@agencyfund) 's Twitter Profile Photo

🔍 How can social sector leaders access decision-relevant data faster? One way is with Ask-A-Metric (AAM), a tool built by IDinsight to help reduce technical barriers to data access and use. Join us with co-hosts Project Tech4Dev and Kabakoo Academies for a dynamic

🔍 How can social sector leaders access decision-relevant data faster?

One way is with Ask-A-Metric (AAM), a tool built by <a href="/IDinsight/">IDinsight</a> to help reduce technical barriers to data access and use.

Join us with co-hosts Project Tech4Dev and <a href="/KabakooLabs/">Kabakoo Academies</a> for a dynamic
IDinsight (@idinsight) 's Twitter Profile Photo

#AI is increasingly being relied upon by decision-makers because the technology has proven efficiencies. But for decisions to be unbiased, accurate and equitable, the data used to train ML models must be high-quality and representative. As our teams blaze the trail for AI use in

#AI is increasingly being relied upon by decision-makers because the technology has proven efficiencies. But for decisions to be unbiased, accurate and equitable, the data used to train ML models must be high-quality and representative.

As our teams blaze the trail for AI use in